Reviewerly/exHarmony huggingface dataset:
The burden of being a Teacher and their roles in motivating passive students

People learn through their entire lives. They constantly improve their knowledge and develop. Every person should have the chance to get a higher degree, gain new knowledge and experience in today’s globalized world. I think that a college or university education should be available to all students because every person has the right to choose the way to self-perfection. For improving all the opinions, there is a primary and demanding occupation stands, no one can be surprised if we say it is teachers-occupation. The government is striving to enhance their roles, and  challenging them to be effective in education so, many attempts such as increasing their salaries, supplying teachers with necessary materials are being carried on.
Welcome Mission Critical Cloud

To remain relevant for our customers, it is important to innovate everything we do to deliver our services. In 2012, Schuberg Philis embraced Cloudstack as part of those innovations. A vendor agnostic, open-source, high-quality and controlled environment for our Infrastructure as a Service layer. Being part of this community has given us a lot of freedom. It has also taught us that we needed to take things in our own hands and luckily this is possible in open source. In 2016, we decided to fork the Cloudstack code base and continue ourselves. This chapter is originally drafted as a blog post written by Arjan Eriks.
Research Guides: Research Data Management : Organize Data

This guide will help researchers with managing research data as well as preparing for data management plans required by funders.
A study on the Process of Conceptual Change of Communities of Practice

이 연구는 최근 공동체성 복원에 대한 사회적 요구에 따라 다양한 삶의 영역에서 발현되고 있는 실천공동체(Communities of Practice: CoPs)의 역사적인 개념 변화 과정을 개념지도로 시각화함으로서, 모호한 실천공동체의 개념을 정립하고, 통합적인 시각을 갖기 위한 목적으로 이뤄졌다.연구 문제는 첫째, 시대별로 실천공동체의 개념은 어떻게 달라져 왔는가, 둘째, 실천공동체의 개념지도는 어떻게 나타나는가, 셋째, 실천공동체 개념의 변화는 향후 실천공동체 연구 및 현장에 무엇을 시사하는가이다. 연구 목적을 달성하기 위해 1990년대 전후부터 현재까지 실천공동체 개념을 논의한 주요 학자들의 문헌을 분석하여 3개의 연대별로 시대적 배경, 기저이론, 실천공동체 구성요소(영역, 상호참여, 실천, 학습환경)가 변화된 과정을 개념지도(concept map)로 작성하였다. 연구결과, 실천공동체는 시대적 배경과 이론의 변화를 반영하여 궁극적으로 사회적 학습시스템의 개념으로 확장된 것으로 나타났다. 실천공동체의 개념은 정보기술의 발달과 일터 환경의 유연화 등의 시대적 흐름에 따라 사회학습시스템 이론을 기반으로 실천공동체의 영역, 상호참여, 실천, 학습환경의 개념이 ‘다층차원의 네트워크를 통한 주도적 참여’와 ‘사회적 실천을 통한 정체성 발견’, ‘사회적 책무성 반영’으로 변화 및 확장된 것으로 나타났다. 실천공동체는 사회적 공간에 존재하며, 구성원들이 사회적 책무성을 기반으로 주도적으로 참여함으로써, 자신의 정체성과 역량을 찾아가는 지속적인 학습의 과정으로 개념화됨으로서, 평생교육의 방향으로 발전되고 있음을 알 수 있었다. 끝으로 향후 실천공동체 연구 및 현장에 주는 시사점과 제언을 제시하였다.This study visualized the historical process of conceptual change of the Communities of Practice (CoPs) by concept mapping. The first research question was how the concept of the CoPs has changed by age, second, how the concept map of the CoPs appears, and third, what does the change in the concept of CoPs suggests for research and practice in the future. In order to achieve the research objectives, we analyzed the literatures of major scholars who discussed the concept of the CoPs from around the 1990s to the present, the periodical background, the underlying theory and the components of the CoPs (domain, mutual participation, practice, and learning environment) in three eras. As a result of the study, it was found that the CoPs was ultimately extended to the concept of the social learning system by reflecting changes in the background and theories of the times. The concept of the CoPs is based on the theory of social learning system based on the development of information technology and the flexibility of the workplace environment. The concept of the domain, mutual participation, practice, and learning environment is leading through a multi-dimensional network. It has been changed and expanded with participation, discovering identity through social practice, and reflecting social responsibility. Finally, suggestions for future CoPs research and fieldwork were presented.
Self Embedding Watermarking pada Citra Digital

Digital watermark is a sign embedded in the digital media, such as images, audio, or video. Digital watermarks typically used to identify ownership of the copyright  of digital media. Digital watermarks may be used to verify the authenticity or integrity of the carrier media. Self-embedding means insert a duplicate of a digital image, into itself. Self-embedding can be implemented as watermarking. This modification will provide the advantage that the introduction of area changes / media damage if it fails to verify the authenticity of the digital media. Duplicates of the digital image is made, by choosing 2 MSB, using selective Bitplane, then pasted on the LSB digital image itself. In this study produced a self-embedding application, which can detect changes in the digital image. The results show that the technique of self-embedding and selective bitplane can be used to verify authentication or integrity, and also the detection of the location of the damage on a 24-bit color digital image.
A Survey of Swarm Intelligence for Task Scheduling in Cloud Computing

In the last few decades, a novel branch of intelligent computation algorithms has been inspired by a swarm intelligence theory which imitates the behavior of animals. These algorithms are successfully applied to solve many kinds of simple and complex problems in several fields such as optimization problems, pattern recognition, image processing, features section, and task scheduling in cloud and parallel computing. Cloud computing has not only become the preferred environment for several companies, but also helps others to overcome many server-related issues by utilizing characteristics such as reliability, flexibility, high scalability, and security. Therefore, many intelligent computation algorithms are used to improve this environment. In this chapter, an overview of swarm intelligence for solving the scheduling problems of tasks in cloud computing is presented, including particle swarm optimization, cat optimization algorithm, artificial bee colony, lion optimization algorithm, whale optimization algorithm, bat algorithm, gray wolf optimizer, cuckoo search algorithm, hybrid swarm algorithms, and multi-objective swarm optimization. All these algorithms are described and presented with their achievements in solving task scheduling issues in cloud computing.
Service traceability in SOA-based software systems: a traceability network add-in for BPAOntoSOA framework

BPAOntoSOA is a generic framework that generates a service model from a given organisational business process architecture. Service Oriented Architecture (SOA) traceability is essentially important to facilitate change management and support reusability of an SOA; it has a wide application in the development and maintenance process. Such a traceability network is not available for BPAOntoSOA framework. This paper introduces an ontology-based traceability network for BPAOntoSOA framework that semantically generates trace links between services and business process architectural elements in both forward and backward directions. The proposed traceability approach was evaluated using the postgraduate faculty information system case study in order to assess the framework behaviour in general. As a continued evaluation effort, a group of parameters have been selected to create an evaluation criterion, which was used to compare the BPAOntoSOA trace solution to one of the most related traceability frameworks, STraS traceability framework.
Implementation on Voice based SQL query Generation using NLP

This system has been developed to enable secure access of data to a voice-based user interface (UI) by enabling voice-based authentication and integration with an existing Natural Language Processing (NLP) system. We address the question of how to improve the fetching the results from query results. Traditional predefined query forms are not able to satisfy various ad-hoc queries from users on those databases. Here, we propose Machine learning based technique to generate the SQL query based on user voice, a novel database query form interface, which is able to dynamically generate query forms.
Extending Visual Studio

In this chapter, we will learn about the extensibility model of Visual Studio. To do so, we will look at the Visual Studio user interface and its software development kit (SDK) and check out the extensibility points available to us. We will then develop a basic extension for a custom command and see how it can be integrated in a code window, tool menu, and solution explorer. We conclude this chapter by discussing some potent questions around command extensibility. By the end of this chapter, we will understand the fundamentals of Visual Studio Extensibility and have developed a basic extension giving us a solid foundation to create the real-world extensions for our beloved IDE.
Decision Support System to Determine Uang Kuliah Tunggal (UKT) by Combining Naïve Bayes Classifier and Fuzzy-TOPSIS

Abstract Uang Kuliah Tunggal (UKT) is a portion of the single tuition fee that is borne by each undergraduate student at a state university in Indonesia. UKT is the number of fees that have to be paid by students in each semester. Basically, UKT is implemented to impose tuition fees according to the income and the condition of students’ families. However, there is an issue in regard to the inappropriate classification of UKT. This issue is caused by several factors such as manual method is still used in determining UKT Classes and there is likely an element of subjectivity in determining UKT Classes of new students. Based on these issues, a decision support system that can determine UKT Class of new students is needed. The Naïve Bayes Classifier (NBC) method is used to classify data into eight UKT Classes. Whereas Fuzzy-TOPSIS is used in the optimization selection process of UKT Class 1 to 8. This method was chosen for its capability in choosing the best alternative out of several possibilities, in this case, the intended alternative is the most suitable new student to be selected in UKT Class based on six predetermined criteria. Research results show that the NBC Model can identify UKT groups of students with mean values of precision and recall testing are 77.8% and 77.8% and the model accuracy is 77.8% as well. In optimization selection process of UKT using Fuzzy-TOPSIS results obtained the percentage of UKT 1 group recommendations was 5.33%, UKT 2 was 5.33%, UKT 3 was 10.22%, UKT 4 was 24.89%, UKT 5 was 24.89%, UKT 6 was 10.22%, UKT 7 was 10.22% and UKT 8 was 8.00%. Based on the results above, it can be concluded that the combination of Naïve Bayes Classifier and Fuzzy-TOPSIS can be implemented for determining the UKT Classes. Then the recommendations of the UKT Classes can be considered in determining the UKT Classes of students for the Decision-maker.
Research Guides: TCC Libraries Material Pick-up: Requesting Items

Instructions for checking out items from TCC Libraries including requesting an item, cancelling a request, and material pick-up instructions. Using the online search tool to request items.
Exploration of the Ecological Teaching Strategy for the Chinese Language in the Teaching Environment of Internet Cloud Platform

Abstract “Internet” education is a new form of education where Internet technology is combined with the education field. As a traditional discipline, Chinese language courses inevitably have a number of problems to be solved in the curriculum reform process. In this paper, the causes for the imbalances in the construction and operation of the ecological teaching mode are analyzed based on the Internet cloud platform environment. A teaching mode construction plan based on the mind map is proposed to provide a beneficial reference for the healthy and sound development of Chinese language teaching.
Use of the Science Technology and Society (STS) model with the help of Facebook in science learning for junior high school students

Abstract Research has been conducted to investigate the influence of the Science Technology Society (STS) learning model which is assisted by social media Facebook (FB) in science learning. This research was conducted in a group of junior high school students in Tondano, North Sulawesi, Indonesia. The research method is a Quasi-Experiment Posttest-Only Control Group Design. The experimental group was treated with the STS learning model assisted by FB, and the control group with lectures, discussions, question, and answer. The number of samples in the experimental group consisted of 25 students and the number of samples in the control group was 25 students. The results of the statistical analysis concluded that there was an influence of the STS learning model with the help of Facebook social media on improving student learning outcomes in science learning in junior high school students. The research data showed that the average post-test score of student learning outcomes in the experimental group was 88.5 higher than in the control group score was only 68.9. The implication of the research results is that the use of Facebook social media in the learning process will make teachers and students interact not only in the classroom. In addition, the STS learning model arouses students’ interest in science learning, especially related to strengthening scientific literacy
Developing Real-World Extensions for Visual Studio Editor

So far we have not extended the core part of Visual Studio that is used most often by the developers – the code editor. The Visual Studio editor offers a rich set of extension points, and most of its parts are extensible via the Managed Extensibility Framework (MEF). In fact, there are so many extensibility points exposed by the editor that covering each of these in details would require a book in itself. Fortunately for us, Microsoft has already documented these extensibility points and features in great depth. In this chapter, we will discuss the extensibility points of the Visual Studio editor and develop extensions for code analysis, fixes, and refactoring.
Research Guides: 2020 Student Research Symposium: Environmental Science: BC Archives Repository

Welcome to the Spring 2020 Virtual Poster Session, hosted by the University/College Library of Broward College
Research on the Algorithm of Online Route Re-planning for UAV Formation

Abstract In order to solve the real-time and robust problem of online flight path re-planning when UAV encounters new threat sources in the course of navigation, an online flight route re-planning algorithm based on sparse A* algorithm is proposed. Based on the threat model of UAV, the online route re-planning strategy is analyzed. When the UAV detects a new threat in the course of navigation, according to the current position of the UAV formation and the position of the threat source, a route that can safely bypass the threat source is quickly re-planned. In order to meet the requirements of real-time and robustness, the node expansion and update strategy of the improved sparse A* algorithm and the hierarchical planning combined with the size step size are adopted. The simulation system of UAV formation navigation is established to verify the process of online route re-planning. The number of expansion nodes and convergence time of algorithm before and after the improvement are compared, and the track accuracy of fine planning based on rough planning is compared. The experimental results show that the improved algorithm can speed up the search speed and meet the real-time requirements of online route re-planning.
Making Use of NXt to Nothing: The Effect of Class Imbalances on DGA Detection Classifiers

Numerous machine learning classifiers have been proposed for binary classification of domain names as either benign or malicious, and even for multiclass classification to identify the domain generation algorithm (DGA) that generated a specific domain name. Both classification tasks have to deal with the class imbalance problem of strongly varying amounts of training samples per DGA. Currently, it is unclear whether the inclusion of DGAs for which only a few samples are known to the training sets is beneficial or harmful to the overall performance of the classifiers. In this paper, we perform a comprehensive analysis of various contextless DGA classifiers, which reveals the high value of a few training samples per class for both classification tasks. We demonstrate that the classifiers are able to detect various DGAs with high probability by including the underrepresented classes which were previously hardly recognizable. Simultaneously, we show that the classifiers' detection capabilities of well represented classes do not decrease.
Research on multi-core DSP cooperative control system in environmental protection equipment

Abstract Traditional multi-servo motor control systems have the problems of poor output stability in environmental protection equipment, weak robustness, and low control ability. Based on this, the research of multi-servo motors control systems based on FPGA are proposed. The paper Construct a parameter distribution models on multi-servo motor control, using motor terminal voltage, current, and back-EMF as control constraints, calculate the difference between the output currents of the multi-servo motors, and construct a saturation function to analyze the multi-servo motor control objective function. Sampling phase current signal and PWM duty cycle as modulation parameters, combined with fuzzy adaptive PID control method to control the output robustness of multiple servo motors, calculating the equivalent mechanical power and equivalent electromagnetic power of multiple servo motors. The optimized parameter adjustment method performs self-tuning processing of the motor output, and the transient stability adjustment of the multi-servo motor is performed based on the method of the average terminal voltage analysis to realize the optimal design of the multi-servo motor control law. The test results show that the output stability of the output of the multi-servo motor control system using this method is better, the motor control is more robust and the control ability is higher.
A STUDY VALIDATING ROBUSTNESS FORVARIOUS ATTACKS ON DIGITAL VIDEOWATERMARKING TECHNIQUES

In this paper, a review is presented of academic literature regarding validating robustness forvarious attacks on digital video watermarking techniques. As of late, the explosive growth of theinternet has expanded rapidly the accessibility of computerized content, such as sound, images, andvideo files to society at large. Like we've seen before, vision security problems and sound data arebecoming increasingly relevant and a significant number of copyright owners are worried aboutensuring that their knowledge or work is not duplicated. There is a need for some serious researchto ensure the availability of multimedia information while protecting the intellectual property ofauthors, distributors or basic owners of such data. That was an exciting challenge and is probably abig reason why so much interest has been forced to pay to integrate relevant images as well asvideo security mechanisms for different types of attacks. The various digital video watermarkingtechniques proposed by various authors and they provide robustness only for few attacks, it isrequired to provide the robustness for various attacks like MPEG-2 compressed video, medianfiltered, small rescaled, and rotational videos. In this, a review is addressed to analyze the variousmethods provided robustness for all types of attacks. Most of the authors were proposed goodrobustness to digital watermarking techniques for numerous attacks.
Conversational Advisors – Are These Really What Users Prefer? User Preferences, Lessons Learned and Design Recommended Practices

The usability of interactive voice response systems (IVRs) has been shown to be challenging for a variety of reasons, including complex menu structures, lengthy menu options to remember, and long wait times for a human representative. Conversational advisors allow users to interact more naturally in a more human-like and conversational manner by using natural language processing, artificial intelligence and machine-learning technology. In this article, two user studies will be discussed examining user performance and preferences between a variety of call flows that incorporate conversational advisors for customer support. We will discuss the findings, and review some lessons learned and recommended practices for designing conversational advisors, along with the benefits and challenges in using them for customer support versus using a human advisor. The attributes that make for effective conversational advisors will also be discussed.
Image Classification by Reinforcement Learning with Two-State Q-Learning

In this paper, a simple and efficient Hybrid Classifier is presented which is based on deep learning and reinforcement learning. Q-Learning has been used with two states and 'two or three' actions. Other techniques found in the literature use feature map extracted from Convolutional Neural Networks and use these in the Q-states along with past history. This leads to technical difficulties in these approaches because the number of states is high due to large dimensions of the feature map. Because our technique uses only two Q-states it is straightforward and consequently has much lesser number of optimization parameters, and thus also has a simple reward function. Also, the proposed technique uses novel actions for processing images as compared to other techniques found in literature. The performance of the proposed technique is compared with other recent algorithms like ResNet50, InceptionV3, etc. on popular databases including ImageNet, Cats and Dogs Dataset, and Caltech-101 Dataset. Our approach outperforms others techniques on all the datasets used.
The Development and Evaluation of Experience-Based Factory Model for Software Development Process

Knowledge, and experiences in software development have been accumulated over time throughout the project lifecycle. Previous studies have shown that the management of knowledge and experiences in software development has always been an issue. Therefore, the knowledge transfer and information flow are inefficient, misinterpretation, and inconsistencies always occur between individuals or teams, and the organization fails to learn from past projects. It is understood that efficient knowledge and experience management for software development organizations is crucial for the purpose of sharing and future reuse. This paper discusses the prototype development for a proposed model, which is based on the experience factory approach, to manage knowledge and experiences for the software development process. Discussions include the system functionalities and design, infrastructure requirements, and implementation approach. The efficiency and effectiveness of the prototype are evaluated as survey research based on Jennex & Olfman knowledge management success model. Rasch analysis is used for data reliability and validity. Results show positive feedback on the model’s efficiency and effectiveness. Additionally, as agreed by most respondents, the top three of the model contributions are: to encourage learning organization, to prevent knowledge loss and to aid in decision making.
What is the shear equivalent of a P-wave? A semantic analysis of geoscientific corpi

Disclaimer Text and Data Mining. Any automated analytical technique aimed at analysing text and data in digital form in order to generate information including - but not limited to - patterns, trends and correlations (so-called Text and Data Mining) may only be applied if it is done by a research organisation or cultural heritage institution solely for the purpose of (non-commercial) scientific research as mentioned in Clause 3 of Directive (EU) 2019/790 (the Digital Single Market Directive) and Clause 15n of the Dutch Copyright Act [Auteurswet]. Text and Data Mining for commercial purposes is not allowed; all rights in this respect are reserved pursuant to Clause 4 paragraph 3 of the Digital Single Market Directive and Clause 15o paragraph 1 of the Dutch Copyright Act.