Reviewerly/exHarmony huggingface dataset:
Mobile Big Data Analytics for Human Behavior Recognition in Wireless Sensor Network Based on Transfer Learning

Big data analysis of human behavior can provide the basis and support for the application of various scenarios. Using sensors for human behavior analysis is an effective means of identification method, which is very valuable for research. To address the problems of low recognition accuracy, low recognition efficiency of traditional human behavior recognition (HBR) algorithms in complex scenes, in this paper, we propose an HBR algorithm for Mobile Big data analytics in wireless sensor network using improved transfer learning. First, different wireless sensors are fused to obtain human behavior mobile big data, and then by analyzing the importance of human behavior features (HBF), the dynamic change parameters of HBF extraction threshold are calculated. Second, combined with the dynamic change parameters of threshold, the HBF of complex scenes are extracted. Finally, the best classification function of human behavior in complex scenes is obtained by using the classification function of HBF in complex scenes. Human behavior in complex scenes is classified according to the HBF in the feature set. The HBR algorithm is designed by using the improved transfer learning network to realize the recognition of human behavior in complex scenes. The results show that the proposed algorithm can accurately recognize up to 22 HBF points, and can control the HBR time within 2 s. The human behavior false recognition rate of miscellaneous scenes is less than 10%. The recognition speed is above 10/s, and the recall rate can reach more than 98%, which improves the HBR ability of complex scenes.
Classifying Latent Profiles of Career Motivation based on Self-Determination Theory for University Students and Differences in Career Adaptation and Job Search Burnout by the Profiles

Objectives This study aimed to classify latent profiles of career motivation based on self-determination theory for university students and verify differences in career adaptation and job search burnout by the profiles in South Korea.&#x0D; Methods The survey data of 683 university students in Seoul, Korea, were analyzed in the study. Latent profile analysis was conducted to classify latent profiles of career motivation, and one-way multivariate analysis was conducted to verify the differences in career adaptation and job search burn out by the profiles.&#x0D; Results Career motivation were classified into three types of profiles which were ‘normal’, ‘self-determined’, and ‘non self-determined’. Career adaptation was significantly higher in the order of ‘self-determined’ type, ‘normal’ type, and ‘non self-determined’ type, while job burnout was significantly higher in the order of ‘non self-determined’ type, ‘normal’ type, and ‘self-determined’ type.&#x0D; Conclusions The ‘self-determined’ type was found to be a desirable type with the highest career adaptability and lowest job search burnout. It is necessary to find ways to increase self-determined career motivation in career field for career development of university students.
The Realization Process and Change of the Picture Book Parenting Meeting Weaved by Mothers and a Professor of the Dept. of Early Childhood Education

Objectives The purpose of this study was to explore the realization process and change of picture books parenting meeting weaved by mothers of young children and a professor of the Dept. of early childhood education.&#x0D; Methods The study participants were three mothers who participated in the picture book parenting meeting and a professor of the Dept. of early childhood education who was in charge of parent education and children's literature education for more than 10 years at a university. Data were analyzed for researcher's observation, individual and group interviews, discussion during picture books parenting meeting.&#x0D; Results According to the results of the study, First, it appeared as establishing a foundation for cooperation and implementing between mothers and a professor of the Dept. of early childhood education : 1) starting from worries and expectations, 2) meeting, and establishing a positive relationship, 3) weaving together based on sharing and practice, 4) feeling a sense of accomplishment, and the expectation of another beginning. Second, it appeared as the change in the experience of picture books parenting weaved by the study participants was shown to be a change through the mother's experience of picture books parenting and a change through the professor's support for picture books parenting.&#x0D; Conclusions It is hoped that this case weaved by mothers and a professor who have shared interest and concerns about picture books parenting will be a little help to the educational lives of parents and educators who have similar concerns and expectations.
Discussion on the Cultivation of Architectural Talents in Applied Universities in Digital Transformation

Under the background of digital economy development, digital transformation has become the key direction of transformation and upgrading of traditional architectural design enterprises, which has improved the ability requirements of the society for construction employees.Application-oriented universities, as the cradle of training skilled talents in construction industry, are facing greater challenges.Combined with the characteristics of the industry, this paper discusses the practical dilemma of building talent training in China, and puts forward some appropriate suggestions.Application-oriented colleges and universities should set up course content and teaching mode according to the characteristics of the industry, and cooperate with each other to improve the level of information teaching.In order to enhance the supply of vocational education talents to the industrial demand of the adaptation.
A Resource Adaptive Secure Aggregation Protocol for Federated Learning based Urban Sensing Systems

Federated learning has been proposed as a privacy-preserving alternative to conventional cloud-based systems dealing with sensitive and private user data. Secure multi-party aggregation improves privacy with protection against inference attacks but involves multiple rounds of communication between participants and the server. This renders existing secure aggregation protocols resource-intensive, especially for urban sensing applications, having a spatiotemporal model which needs to be updated frequently. This paper presents resource adaptive (ReAd) Turbo-Aggregate, a secure multi-party aggregation protocol for dynamic spatiotemporal applications, which provides adaptive space and time complexity to match participating users’ network, processing, and battery resources.
Relation Classification Model Performance as a Function of Dataset Label Noise

The central question that this paper address is: How does the performance of a supervised model vary with respect to the label noise in the testing and training dataset? Answering this question is crucial for many real-world applications for two main reasons. First, most datasets used for training large supervised models such as Deep Neural Networks (DNNs) are crowd-sourced. Such datasets are known to have significant label noise due to multiple factors such as the complexity of the annotation task and low wages for crowd-sourced annotators. Second, these crowd-sourced datasets are large. Reannotating such large datasets is a time-consuming and costly process. Our work aims to understand the relation between the cost of data reannotation and the performance of supervised models. Understanding this relationship can be helpful while planning for data reannotation.
Adaptive Selection Algorithm of Paragraph Selection Structure Based on Complex Data Type

In the automatic generation of standard documents, the replacement method of template is cumbersome and difficult to modify and maintain in the later stage when dealing with the selection structure in the paragraph template.To solve this problem, an adaptive paragraph selection structure selection algorithm based on complex data types is proposed.On the basis of the tree structure, each node is abstracted into a class, selection nodes are set, and attributes and methods are set for the selection nodes.The deletion and retention of nodes in the paragraph template are completed through the attributes and methods of the selection nodes.The experiment shows that it has a good effect in paragraphs with multi branch sentences.
Query-Focused Re-Ranking to Enhance the Performance of Text Entailment and Question Answering

Transformer-based models have dramatically improved performance of various natural language processing tasks like question answering, fact verification, topic-driven summarization and natural language inferencing. However, these models can’t process input context longer than their token-length limit (TLL) at a time. Given a large document however, the required context may be spread over a larger area and also may not be restricted to contiguous sentences. Existing methods fail to handle such situations correctly. In this paper, we propose a method to handle this issue by detecting the right context from a large document before performing the actual query-context text-pair task. The proposed method fragments a long text document into sub-texts and then employs a cross-encoder model to generate a query-focused relevance score for each sub-text module. The actual downstream task is performed with the most relevant sub-text chosen as the context, rather than arbitrarily selecting the top few sentences. This extricates the model from the traditional way of iterating over TLL window size text fragments and saves computational cost. The efficacy of the approach has been established with multiple tasks. The proposed model out-performs several state of the art models for the tasks by a significant margin.
Analyzing a Practical Arts Subject Curriculum Development Project: Learning Experiences of Students at the University of Education

Focusing on students, this study explored the experiences and meanings of practical arts education curriculum development with project learning. For this purpose, a literature analysis and interview methods were employed. The literature analysis was conducted based on the results of a team project in the practical arts education course among second-year students at A-University of Education. The participants included seven students of the practical arts education course, all of whom were interviewed. Their results were then qualitatively analyzed. The main findings were as follows.&#x0D; First, the development of the practical arts subject curriculum by University of Education students was meaningful in that it provided fresh ideas about the content structure and framework of the practical arts subject curriculum at the college level. However, the practical arts education curriculum development was not sufficiently deep. Second, students of the College of Education recognized that the systematic flow of the overall team project was important. In addition, there were requests to expand the degree of student choice and autonomy, introduce a fair individual evaluation system, and strengthen factors for vitalizing team projects. Third, through this course, students of the University of Education improved their understanding of the practical arts education curriculum, increased their ability to apply the curriculum development model, and gained more positive attitudes toward the curriculum as teachers.&#x0D; Based on these results, suggestions are offered for the practical arts education curriculum. Follow-up research is also recommended among students at the College of Education.
Analyzing Practical Arts Textbooks to Determine the Types of Questions Asked on SW Programming Units

This study analyzed practical elementary school textbooks to ascertain the types of questions asked on software (SW) programming units, with the aim of identifying a writing direction for an impending curriculum revision. In this context, the scope of analysis was limited to units corresponding to “programming structures and elements.” To classify relevant questions, we used a framework from a previous study that analyzed types of questions pertaining to “SW and robot unit.” The results were as follows.&#x0D; First, the ratio of closed questions (71.03%) was approximately 2.45 times higher than the ratio of open questions (28.97%). Second, the characteristics of the type of question by publisher were the same in that all six publishers had a higher closed questions than the open questions ratio, but there were publishers who did not use memory questions(A, D) and divergent thinking questions(C) depending on how they were composed. Third, our analysis of the types of questions found in each unit component showed that most recognitional questions were provided in the introduction and developing sections, while most evaluation questions were provided in the organizing section.&#x0D; To summarize, we found a higher ratio of closed questions (which restrict student thinking) than open questions These results are expected to be used as basic data for writing SW programming units for practical arts textbooks.
Based on the Sustainable Development Goals (SDGs) and ESG Consumer type recommendation and design direction of brand promotion

The world is now in full swing to achieve the Sustainable Development Goals (SDGs) set by the United Nations. Companies are giving ethical influence by delivering SDGs practice information to consumers through ESG management. Consumers who use goods or services produced by companies are also subject to social responsibility (CSR). In order to fulfill this responsibility together, I looked into the types of consumers through the Persona profiling report of brand and PR, and found that women in their 30s and 40s enjoy digital and conveniently adjust their self-centered environment. , advertising and promotion factors, and convenience factors in order of use. We were able to confirm the data that consumption is based on the image of the brand rather than price and quality. Although there are various design activities such as product production and service, we will continue to help research eco-friendly and ethical consumption as design plays a leading role by referring to consumer type recommendations according to the characteristics of each brand.
A Study on the Teaching and Learning Method of Art Appreciation of Elementary School Students Subject to Learning Support Based on Positive Psychology

This study sought to find out the characteristics of students subject to learning support and to prepare an art appreciation learning plan based on positive psychology to improve basic education in the speaking, listening, and writing areas of elementary school students. Through literature research, we found the meaning of art appreciation education, starting with the understanding of students subject to learning support, and eventually, based on Seligman's positive psychology, we designed an art appreciation teaching and learning process using emotion cards that can explain his thoughts and feelings. In conclusion, art appreciation learning using the strengths of positive psychology is meaningful in encouraging individual and self-directed learning for students, and it is also meaningful in art appreciation education activities that provide positive emotions as an alternative to enhancing basic communication opportunities.
A Study on Utilization of Computational Thinking for Implementing Creativity

This study aims to inquire into creative manifestation of people without experience in design focused on computational thinking with a view to improving problem-solving abilities, in times of the increasing needs for problem-solving abilities and creativity due to growing complex problems of today. Though creativity is usually manifested by emotions and intuition of designers, it requires systematic computational thinking based on Big data, AI and Internet-based coding. As a way of strengthening problem-solving abilities, this study intends to examine how logical and quantitative computational thinking influences to improve creativity in design. For the purpose of this, through literature review regarding computational thinking, way of thinking of designers, design thinking and creativity, this study conducted thinking based on computer program oriented to students of school with gifted education, who do not have science-based design experience. This study aims to stop the quality investigation of left-brain and right-brain, scratch thinking and design thinking and ways to gain benefits, stop using them, and target science-based gifted school students who do not have a design environment. A social enterprise logo using Adobe Illustrator. After specifying the design, it was divided into four personas based on the contents of the interview. Through this, it was derived that the students obtained satisfaction during the design process by helping to solve problems through idea implementation, automation of implementation, materialization of implementation, and abstraction of implementation.
In Support of V. Afanasyeva’s Open Letter to Russian Minister of Education O.Y. Vasilieva

The author writes in support of Dr. Afanasyeva’s open letter to Russian Minister of Education O.Y. Vasilieva. He agrees with Dr. Afanasyeva’s assessment of the current problems facing the Russian academic community in terms of both the awarding of degrees and the process of publishing peer-reviewed articles. The reduction of publicly funded universities and the commercialization of academia have had a detrimental effect on academic standards. While relaxed academic standards have led to plagiarism and improper accreditation, the over-bureaucratization of the academic process has also led to unnecessary procedures that often stymie scientific research and the publication of legitimate research.
Characteristics of technology-facilitated domestic violence

While all crime is harmful in terms of its impact on survivors, their friends and loved ones, and the surrounding community, intimate partner abuse (IPA) is one of the most insidious forms of deviance that crosses all geographic and socio-cultural boundaries. Although practitioners and scholars have increased knowledge and understanding about IPA throughout the years, it continues to evolve as individuals increasingly rely on cyberspace and technology in social life. More specifically, given abusers’ recognition of that reliance, there is increasing innovation in the methods by which survivors are trapped within an offline and online web of coercive control. As outlined in this chapter, research studies show that abusers have leveraged cyberspace and technology to engage in cyber intimate partner abuse (hereafter cyberIPA) via cyberfraud, cyberharassment, cybersexual abuse, and cyberstalking. Unfortunately, cyberIPA remains understudied within cybercriminology, despite these events being categorically different from instances between acquaintances or strangers.
Blockchain Technology Effects on Healthcare Systems Using the IoT

Due to the introduction of the blockchain via Bitcoin, research has been underway to extend its use to other sectors. For example, blockchain has significant implications for healthcare systems, and it effectively makes the study chapter. Because it is relatively new, researchers and practitioners in health informatics are always trying to keep up with the ever-expanding research in this area. A systematic review of blockchain technology implications in the healthcare system is presented in this chapter. It is based on PRISMA guidelines for examining metadata analyses of selected studies to identify, extract, and analyze relevant publications across specific databases. Based on the review, several studies have proposed blockchain technology in the healthcare system, showing exciting results and solving critical challenges. The Systematic Literature Review discusses blockchain’s application implications for modern healthcare systems and how it is used to improve standard practices associated with handling, transferring, and sharing medical data and personal health records. However, no prototype implementations based on the Internet of things or studies have been carried out to check if these technologies are effective. Furthermore, the study highlights the recent progress in the development of healthcare blockchain based on the Internet of things, their limitations, and the areas where research is needed. As a result, more research on blockchain technology implications is still required to customize better and evaluate healthcare systems.
Topics and Music Performance

It is obvious that so-called topic theory has, in recent years, achieved a central role in studies of musical style and aesthetics. In most conservatories, young music students do not like music theory and try to get through those classes with minimum effort. The reason is that traditional music theory teaching has not paid attention to how theory has an impact on musical praxis, performance. Musical form is understood as a collection of quite abstract ideas. In this respect, one has to admit that the introduction of topics to music analysis means that the whole rich realm of musical meaning or signification is allowed to enter the field of absolute music. In a situation where such theories as set theory, Schenkerian analysis, cognitive doctrines and so forth dominate, this has meant a rather radical step and paradigmatic shift.
Cloud Technology

Cloud computing is the delivery of computing resources over the Internet. Some examples of these resources are storage space, databases, software applications, and processing power. Companies outsource these resources for many reasons. The users of these cloud resources can access them anywhere they have an Internet connection and a device. Cloud computing allows users to use expensive computer software on the cloud instead of purchasing this expensive software and installing them on PCs. Hence, cloud computing technology offers cost-efficient and flexible business models. Besides, storing essential data in the cloud provides an effective solution for data safety. Companies can focus on their core business and manage their processes more effectively by using cloud computing technology.
Anomaly Detection for Lung CT image Using Efficient GAN with Learning Stabilizations

CT (Computed Tomography) screening for detection of early cancer is becoming widespread. The purpose of this study was to develop a computerized method for detecting any lesion in CT images. Our database consisted of lung CT images for 100 abnormal cases and 300 normal cases. In the proposed method, learning stabilization methods were introduced to Efficient GAN (Generative Adversarial Network). The classification accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve of the receiver for the proposed method were 61%, 62%, 60%, and 0.66, respectively. Those evaluation indices were greater than a conventional Efficient GAN without learning stabilizations (44%, 46%, 42%, and 0.44).
A Covariance Matrix Adaptation Evolution Strategy-based Manta Ray Foraging optimization

Covariance matrix adaptive evolution strategy (CMAES) is an excellent local search strategy that does not rely on gradient information. It is widely used in real-valued optimization because it fast converges to the local optimum. In addition, manta ray foraging optimization (MRFO) is an evolutionary algorithm inspired by the manta rays’ three particular foraging strategies which can carry out a good solution for global optimization problems. In this paper, we use CMAES to strengthen the local search ability of MRFO and propose CMAES-MRFO to generate better solutions. The CEC’2017 benchmark functions are employed to test the hybrid algorithm. Experimental results show that the proposed CMAES-MRFO significantly outperforms its original algorithms and some other newly-coming ones.