Reviewerly/exHarmony huggingface dataset:
Optimal Switching and Load Distribution Strategy for Energy Minimization and Performance Optimization of Cloud Data Center

Cloud computing is a promising computing technology utilized in every stage of the business. The cloud offers different services to cloud users from anytime to anywhere, and it is attained with different parameters, like load optimization, resource optimization. Due to the increase in data center, energy consumption has become a major issue in green data centers. The majority of data centers are function using peak load with huge scales. Thus, it is essential for carrying out energy saving in cloud data centers. This paper designed an energy-saving method using fat tree. The proposed techniques optimize the load at different zones of data center and user in the cloud platform. Here, the distribution of load in cloud data centers is performed using Taylor-based Manta Ray Foraging Optimization (Taylor-MRFO), which is an integration of Manta Ray Foraging Optimization (MRFO) and Taylor series. The method utilized different objectives that involve power, load, latency, and bandwidth. With the load distribution, the switching of cloud data center to the desired mode is performed using Actor critic neural network (ACNN). Thus, the dual strategy leads to performance optimization in cloud infrastructure and also in consolidating parallel workload in data centers more effectively. The proposed Taylor-MRFO+ACNN outperformed other methods with minimal energy of 0.553, minimal load of 0.363, and minimal fitness of 0.437, respectively.
일본 내 한국학교 지속가능발전 방안에 대한 연구I - 포용적인 양질의 교육 보장을 위하여 -

This research conducted the survey on the perceptions about K school in Osaka that has the only dispatched principal of the 3 national schools authorized by Korea in Japan. The survey was conducted on parents of middle and high school students of K school in Osaka. The research term is from October 29, 2019 to December 4, 2019. There was 56% return rate with 58 of 103 parents responding. This research analyzed the result of the survey. The results of the survey are : First, the guardians K school hope to make the most of Korean schools and small schools and to promote them more actively. Second, the guardians K school want their students to experience much wider world as a talented person and enjoy the educational courses that contain interest and level of the students. Third, the guardians K school expect K school to have good points of both Japanese and Korean school, to develop proper education curriculums and texts and to conduct a student-oriented class.
Classification of students according to the characteristics and faculty learned by using data classification techniques by decision tree methods Case study of the University of the Thai Chamber of Commerce students

The objective of this research is to classify students according to the characteristics and faculty learned by using data classification techniques by decision tree methods. The sample group is 400 students of the University of the Thai Chamber of Commerce. By data mining, using data classification techniques and relational processes Cross-Industry Standard Process for Data Mining (CRISP-DM) . There are steps starting from defining and understanding the objectives, studying, collecting data, then preparing the data by converting them into data that can be analyzed after that, creating models, checking models and implementing models. In the process of creating the model, the data were analyzed using the decision tree technique based on the Precision and Recall. The results of the research with the accuracy of 67.52% found that (1) Students of the Faculty of Business Administration have defined their own advantages as being able to easily adapt to various situations. Students have the main goal when graduating and have work to do immediately and think that the work done on graduation does not have to be exactly the same as the field that has been studied. ( 2) Students of the Faculty of Accounting have the most favorite subjects, which are language courses and think that the work done after graduation is not necessarily the same as the field that has been studied. ( 3) Students of the Faculty of Science and Technology think that their personality is like a job that uses tools, likes to practice and doesn't like socializing. Students have the main goal that when graduating, must have work immediately and think that the work that has been done after graduation is necessary to match with the field that has been studied. ( 4) Students of the Faculty of Communication Arts have a favorite after-school activity that is walking in department stores and prefer to buy products from online stores. Students think that the work that has been done after graduation is not necessarily the same as the field of study.
ANALISIS KEAMANAN JARINGAN DENGAN ENDEKATAN PROTOKOL AUTHENTICATION HEADER (AH) DAN ENCAPSUATING SECURTIY PAYLOAD (ESP) TUNNELING STUDI KASUS UNIVERSITAS MUHAMMADIYAH PALEMBANG

In a computer network, security in sending and receiving data is very important to ensure that the data sent does not fall to third parties, especially if the data is confidential. For this reason, implementation of methods for securing data on the network is needed. One solution to solving security problems in a public network is to use Protocol Authentication Header (AH) and Encapsulating Security Payload (ESP) tunneling. Protocol AH and ESP Include Protocol in the Internet Protocol Security (IPSec). IP Security is a protocol used to secure the transmission of datagrams in a TCP / IP-based internetwork, IPSec Encrypts data in the same layer as the IP Protocol and uses tunneling techniques to transmit information over the internet or in intranet networks safely. IPSec supports two security communication sessions, namely the Authentication Header (AH) Protocol which serves to offer user authentication and protection from several attacks, the analysis shows that sniffing attacks cannot intercept because the data is encrypted in the view using Wireshark. Kata Kunci : AH, ESP, IPsec,Protocol, Tunneling, VPN
Pemanfaatan Kahoot sebagai quiz game interaktif bagi pendidik di Kabupaten Gowa

The application of E-learning uses the TPACK (Technology Pendagogical And Content Knowledge) framework as a reference for the use of technology in learning that shows the relationship between the three basic knowledge that must be mastered by the teacher, namely technological knowledge, pedagogy, and content is still low. One of them is game-based learning which has the potential to become an effective learning tool that stimulates visual and verbal components that have not been widely used by teachers in schools. One online that appears on the learning platform used in educational institutions is Kahoot. Kahoot is an online application where quizzes can be developed and presented in game format. From the results of a survey conducted by the community service implementation team some time before, it was found that the target conditions of service participants in terms of digital media literacy were still low. The purpose of this pkm activity is to improve literacy skills in the use of Kahoot digital media among educators that lead to improving the quality of the PBM process in order to realize learning that leads to 21st century learning. In the implementation of this training activity, the results obtained are: 1) PKM activities participated by Gowa Al Fityan School Middle School teachers have the ability to use Kahoot Flatform and Google Form as online-based evaluation tools. 2) Assessment in the implementation of the Community Partnership Program activities obtained an average overall score of 4.86 (with good criteria).
Uncertainty quantification in non-rigid image registration via stochastic gradient Markov chain Monte Carlo.

We develop a new Bayesian model for non-rigid registration of three-dimensional medical images, with a focus on uncertainty quantification. Probabilistic registration of large images with calibrated uncertainty estimates is difficult for both computational and modelling reasons. To address the computational issues, we explore connections between the Markov chain Monte Carlo by backpropagation and the variational inference by backpropagation frameworks, in order to efficiently draw samples from the posterior distribution of transformation parameters. To address the modelling issues, we formulate a Bayesian model for image registration that overcomes the existing barriers when using a dense, high-dimensional, and diffeomorphic transformation parametrisation. This results in improved calibration of uncertainty estimates. We compare the model in terms of both image registration accuracy and uncertainty quantification to VoxelMorph, a state-of-the-art image registration model based on deep learning.
Cultural diversity, Intercultural Competence, Tolerance and the Economy: a Review

Cultural diversity is generally a controversial topic in the literature. Whereas some studies proved that it has economic benefits, others denied that. However, it is possible to avoid the costs related to that through enhancing each of intercultural competence, on the level of firms, and social tolerance, on the level of economies. To investigate that, the study used literature review analysis. Based on the literature, cultural diversity plays important role in enhancing innovation and entrepreneurship which are necessary for economic development. However, it may result in different challenges such as a lack of trust and conflict. Therefore, it could be feasible to manage and benefit from cultural diversity in the companies through cross-cultural training as well as cultural diversity management. On the other hand, economies can avoid cultural diversity's costs by adopting the policies and institutions which are necessary for enhancing the level of social tolerance among people.
Product Category Recommendation System Using Markov Model

AbstractProduct recommendation is an intelligence system that is widely used in many industries. In order to recommend products to target customers efficiently, system designers must understand the characteristics of products and customers. In cosmetic industry, position and image of products influence to the customer’s decision. Some customers may stick with the same products, but some of them prefer like to keep trying new things. Thus, it is not easy to promote accurately cosmetics products to the users. Cosmetics advertisements usually come in a form of product lines or categories not just one item. If the marketers can narrow down the group of users who will buy in their preferred product lines, it will reduce cost and increases efficiency of that advertising especially in email marketing since it will not include non-target users. This paper presents a technique for category recommendation using clustering techniques and Markov model. With clustering, it leads the model to be more optimized and calibrated. Markov model can help to scope interested product category of each customer. This system also helped reduce advertising irrelevant products to the users.KeywordsCategory recommendationRecommended systemCosmeticsClusteringMarkov model
초등학생 대상 증강현실 기반 영어 어휘수업의 효과성 분석

This study aims to investigate the effectiveness of English vocabulary class using an augmented reality (AR) application for elementary school students’ cognitive (phonemic awareness and vocabulary ability) and affective (interest, self-confidence, and immersion) domains. Forty-one students participated in the class for 6 weeks (twice a week). Most of them were at a beginner level in English courses. The class for the experimental group (20) was taught using an AR technology and the control group (21) was operated using the traditional method of instruction. The research findings suggest that learning activities based on AR have statistically meaningful effects on enhancing phonemic awareness cognitively and self-confidence affectively. It is encouraging that English classes based the AR application can improve the cognitive and affective domains of young learners with low English skills. This study shows the educational potential and possibilities of learner-friendly AR technologies that can be practically applied to in education classes for elementary school students. Further studies are needed to design more effective teaching and learning models based on augmented reality platforms in English education.
Structural Decompositions of Epistemic Logic Programs.

Epistemic logic programs (ELPs) are a popular generalization of standard Answer Set Programming (ASP) providing means for reasoning over answer sets within the language. This richer formalism comes at the price of higher computational complexity reaching up to the fourth level of the polynomial hierarchy. However, in contrast to standard ASP, dedicated investigations towards tractability have not been undertaken yet. In this paper, we give first results in this direction and show that central ELP problems can be solved in linear time for ELPs exhibiting structural properties in terms of bounded treewidth. We also provide a full dynamic programming algorithm that adheres to these bounds. Finally, we show that applying treewidth to a novel dependency structure---given in terms of epistemic literals---allows to bound the number of ASP solver calls in typical ELP solving procedures.
대학생의 진로 집단프로그램의 참여효과

The purpose of this study was to analyze the effects of college students' participation in a career group program to strengthen their career competency. For this purpose, in this study, we tried to find out what kind of changes in self-efficacy and career barrier perceptions when college students participated in a career program, and to expand their understanding through qualitative data analysis on students' satisfaction and experiences. As a result of pre-post difference analysis on career decision self-efficacy and perception of career barriers, among the sub-factors of career decision efficacy, self-evaluation (t=4.44, p=.000), job information collection (t=4.37, p=.000) ), goal selection (t=5.49, p=.000), future planning (t=4.80, p=.000), and problem-solving (t=4.07, p=.000) were significant at the .001 level. It was found that there was a positive effect. Among the sub-factors of career barriers, lack of job information (t=-6.35, p=.000), lack of self-assurance (t=-5.04, p=.000), indecisive personality (t=-4.43, p=.000) , there was a significant decrease in the perception of career barriers in extrinsic obstacles (t=-1.87, p=.07). As a result of the satisfaction analysis of the participants, the average of 4.84 (SD=.37) on the 5-point Likeard scale for overall satisfaction with the program was very high. As a result of the participatory reflection analysis, the participating students participated in the understanding program in response to the demands for career exploration and self-development and growth, and through participation in the program, self-understanding and reflection on their own characteristics and effective career paths. could understand about In addition, it was found that emotional support was obtained through positive communication and interaction with group members. Therefore, it was found that the effects and experiences of participation in the program were reflected in the pre-post effect analysis, satisfaction, and participation reflections. As described above, the results of this study are expected to be useful in obtaining specific data for the effective operation of a career group program suitable for the characteristics of universities and current students.
TEXTOIR: An Integrated and Visualized Platform for Text Open Intent Recognition.

TEXTOIR is the first integrated and visualized platform for text open intent recognition. It is composed of two main modules: open intent detection and open intent discovery. Each module integrates most of the state-of-the-art algorithms and benchmark intent datasets. It also contains an overall framework connecting the two modules in a pipeline scheme. In addition, this platform has visualized tools for data and model management, training, evaluation and analysis of the performance from different aspects. TEXTOIR provides useful toolkits and convenient visualized interfaces for each sub-module (Toolkit code: https://github.com/thuiar/TEXTOIR), and designs a framework to implement a complete process to both identify known intents and discover open intents (Demo code: https://github.com/thuiar/TEXTOIR-DEMO).
МЕТОД AGILE EARNED VALUE MANAGEMENT ЯК ІНСТРУМЕНТ УПРАВЛІННЯ ВАРТІСТЮ В SCRUM-ПРОЄКТАХ

According to the statistics, the majority of IT projects run 50–150 percent over budget, which indicates the importance of managing its cost. In agile methodologies which are widely used in software development, little attention is given to cost management. Lack of specialized cost management tools in agile practices raises the question of the feasibility of adapting traditional project management methods and techniques. The purpose of the research is to improve the quality of IT projects cost control processes by developing a project cost management model using the Agile Earned Value Management method. The paper discusses the EVM techniques which have been adopted to provide the benefits of traditional EVM in Agile projects. There are some misconceptions that EVM techniques are too difficult to perform effectively on projects implemented using agile approaches (i.e. Scrum framework). The challenges are primarily associated with the fact that the EVM method requires creating a complete description of project tasks and a detailed schedule of their execution at the initial stage allowing accurate estimates of the actual data and monitoring the project progress from start to completion. On the other hand, Scrum emphasizes the need for incremental, multi-level planning and discourages planning software projects down to the lowest level of decomposition in the early stages. The reason for this is the high degree of ambiguity inherent in complex software systems, and the high probability of changes that make fully defining the requirements up front nearly impossible. However, upon closer examination of Sprint attributes, such as fixed duration, fixed backlog, cost measurement of sprint tasks, the ultimate goal of delivering a minimum viable product – leads us to the conclusion that Sprint can be considered as a subproject to which the mechanism of the EVM method can be applied using the same metrics. The paper further summarizes the main provisions and guidelines of the AgileEVM method, based on which its process model is developed. The inputs of the model are initial release baseline parameters and data captured at the completion of each Sprint: Planned Sprints (PS); Planned Release Points (PRP); Budget at Complete (BAC); Points Completed (PC), Points Added (PA), and Sprint Cost (SC). The controls are the AgileEVM method guidelines. The mechanisms are project manager and necessary software (MS Excel, MS Project). At the output of the model we obtain forecast indicators: Estimate to Complete (ETC), Estimate at Complete (EAC), Number of Total Sprints (N), and Release Date (RD). The final conclusion of the conducted research is that the application of the Earned Value Management method to projects implemented with Scrum enables the project manager and the project team with a valuable tool to monitor the progress of their work and to take appropriate measures.
Survey on Virtual Dressing Room

A Virtual Trial Room application utilizing Augmented Reality which enables a client to undertake on virtual garments. The client posture and profundity is followed utilizing the Microsoft Kinect sensor and virtual garments are lined up with the followed client. the clothes moves and adjusts practically and therefore the lighting force of the fabric render is adjusted to coordinate surrounding lighting conditions. The exhibited application enhances related increased reality application by including full client posture following and by utilizing 3D dress models joined with fabric recreation instead of 2D pictures.
Actomyosin in biocomputation

There exist complex mathematical problems that are important in real world applications such as weather prediction, molecular modelling, network route optimization and more. In general, such proble ...
NCU-NLP at ROCLING-2021 Shared Task: Using MacBERT Transformers for Dimensional Sentiment Analysis.

We use the MacBERT transformers and fine-tune them to ROCLING-2021 shared tasks using the CVAT and CVAS data. We compare the performance of MacBERT with the other two transformers BERT and RoBERTa in the valence and arousal dimensions, respectively. MAE and correlation coefficient (r) were used as evaluation metrics. On ROCLING-2021 test set, our used MacBERT model achieves 0.611 of MAE and 0.904 of r in the valence dimensions; and 0.938 of MAE and 0.549 of r in the arousal dimension.
Multisensory processes of experiencing the environment

This podcast interview is available on Spotify. In this episode, I talk about the innovative multi-sensory process of listening to the environment and mapping my soundwalks, which I often use to create my sound work. I begin first by describing the multi-speaker sound system MAAST, which I direct at the University of Kent, at the Department of Music and Audio Technology, and I continue describing the role of space and its re-imagining in my compositions.
Social Annotation with world languages, I Annotate 2021, the conference for open annotation practices and technologies, June 21-25 2021.

Sharing practices with social annotation in world languages teaching and learning. We describe the experience of Social Annotation, using Hypothes.is in Spanish, before and after the lockdown due to the COVID-19 pandemic.
Wisdom Extraction from the English Poetry using SVMs

English poetry is unstructured text data, as each poet follows his style of writing a poem. The poet tries to advise in the form of  Wisdom that expresses the poet's opinion about a specific topic, event, and issue. Wisdom extraction is a new approach in the Text mining field. The biggest problem for people, especially those who are not English native, is to extract wisdom from the poems since it needs a perfect English language. This paper designs an automatic system for extracting wisdom from English poems using support vector machines ( SVM) and two Features Weight Methods, which are Term Frequency (TF) and Term Frequency – Inverse Text Frequency (TF-IDF) on training data. The performance accuracy measured using a confusion metric, where the best result is 76% obtained when the TF-IDF feature was used.
The value evolution of the curriculum in the current context of changes

Its superior value-teleological, normative and axiological evolution reflects and constructively processes the interactive psychological and sociocultural reality, perfectible with concrete effects, realistically anticipated on the learners, as well as on the process itself. Restructuring the school curriculum (framework plans and curricula) is necessary to promote values-based on education, creativity, cognitive skills, volitional skills and action skills, basic knowledge and knowledge skills and abilities of direct use, in the profession, in society and focus the curriculum on the formation and development / diversification of key competences. The curricular review will place greater emphasis on the development of transversal competences, including digital ones, those on sustainable development and socio-emotional competences. The argument for the need to reconfigure the current learning process is to opt for a holistic, transdisciplinary and functional-pragmatic approach to learning outcomes.