Reviewerly/exHarmony huggingface dataset:
A Method to Extract Motion Velocities of Limb and Trunk in Human Locomotion

Human motion monitoring is important in applications of movies, animation, sport training, physical rehabilitation, and human-robot interaction. There is a demand for a simple and easy-to-use method to recognize motions of limbs and trunk. In this paper, we developed a wearable velocity tracking device using two orthogonally-placed micro flow sensors to implement three-dimensional motion velocity measurement. In addition, we proposed a functional link artificial neural network (FLANN) model to extract trunk velocity and relative limb velocity from an absolute limb motion detected by the wearable tracking device according to their different dynamic features. Experiments were conducted to validate the effectiveness of the velocity tracking methodology. Results showed the proposed method with wearable device enables real-time measurements of motion velocities of limb and trunk, which were free of accumulated error, robust for dynamic walking and running, and simple to use.
CDDM: Concept Drift Detection Model for Data Stream

&lt;p&gt;Data stream is the huge amount of data generated in various fields, including financial processes, social media activities, Internet of Things applications, and many others. Such data cannot be processed through traditional data mining algorithms due to several constraints, including limited memory, data speed, and dynamic environment. Concept Drift is known as the main constraint of data stream mining, mainly in the classification task. It refers to the change in the data stream underlining distribution over time. Thus, it results in accuracy deterioration of classification models and wrong predictions. Spam emails, consumer behavior changes, and adversary activates, are examples of Concept Drift. In this paper, a Concept Drift detection model is introduced, Concept Drift Detection Model (CDDM). It monitors the accuracy of the classification model over a sliding window, assuming the decline in accuracy indicates a drift occurrence. A modification over CDDM is a weighted version of the CDDM as W-CDDM.&lt;/p&gt;&lt;p&gt;Both models have evaluated against two real datasets and four artificial datasets. The experimental results of abrupt drift show that CDDM, W-CDDM outperforms the other models in the dataset of 100K and 1M instances, respectively. Regarding gradual drift, the W-CDDM overtook the rest in terms of accuracy, run time, and detection delays in the dataset of 100 K instances. While in the dataset of 1M instances, CDDM has got the highest accuracy using the NB classifier. Moreover, W-CDDM achieves the highest accuracy on real datasets.&lt;/p&gt;
GESTURE RECOGNITION FOR PENCAK SILAT TAPAK SUCI REAL-TIME ANIMATION

The main target in this research is a design of a virtual martial arts training system in real-time and as a tool in learning martial arts independently using genetic algorithm methods and dynamic time warping. In this paper, it is still in the initial stages, which is focused on taking data sets of martial arts warriors using 3D animation and the Kinect sensor cameras, there are 2 warriors x 8 moves x 596 cases/gesture = 9,536 cases. Gesture Recognition Studies are usually distinguished: body gesture and hand and arm gesture, head and face gesture, and, all three can be studied simultaneously in martial arts pencak silat, using martial arts stance detection with scoring methods. Silat movement data is recorded in the form of oni files using the OpenNI ™ (OFW) framework and BVH (Bio Vision Hierarchical) files as well as plug-in support software on Mocap devices. Responsiveness is a measure of time responding to interruptions, and is critical because the system must be able to meet the demand.
A Recommendation Method for Highly Sparse Dataset Based on Teaching Recommendation Factorization Machines

There is no reasonable scientific basis for selecting the excellent teachers of the school’s courses. To solve the practical problem, we firstly give a series of normalization models for defining the key attributes of teachers’ professional foundation, course difficulty coefficient, and comprehensive evaluation of teaching. Then, we define a partial weight function to calculate the key attributes, and obtain the partial recommendation values. Next, we construct a highly sparse Teaching Recommendation Factorization Machines (TRFMs) model, which takes the 5-tuples relation including teacher, course, teachers’ professional foundation, course difficulty, teaching evaluation as the feature vector, and take partial recommendation value as the recommendation label. Finally, we design a novel Top-N excellent teacher recommendation algorithm based on TRFMs by course classification on the highly sparse dataset. Experimental results show that the proposed TRFMs and recommendation algorithm can accurately realize the recommendation of excellent teachers on a highly sparse historical teaching dataset. The recommendation accuracy is superior to that of the three-dimensional tensor decomposition model algorithm which also solves sparse datasets. The proposed method can be used as a new recommendation method applied to the teaching arrangements in all kinds of schools, which can effectively improve the teaching quality.
Inferring Visual Biases in UAV Videos from Eye Movements

Unmanned Aerial Vehicle (UAV) imagery is gaining a lot of momentum lately. Indeed, gathered information from a bird-point-of-view is particularly relevant for numerous applications, from agriculture to surveillance services. We herewith study visual saliency to verify whether there are tangible differences between this imagery and more conventional contents. We first describe typical and UAV contents based on their human saliency maps in a high-dimensional space, encompassing saliency map statistics, distribution characteristics, and other specifically designed features. Thanks to a large amount of eye tracking data collected on UAV, we stress the differences between typical and UAV videos, but more importantly within UAV sequences. We then designed a process to extract new visual attention biases in the UAV imagery, leading to the definition of a new dictionary of visual biases. We then conduct a benchmark on two different datasets, whose results confirm that the 20 defined biases are relevant as a low-complexity saliency prediction system.
Negative Politeness Strategies in “Big Hero 6” Movie

This article describes the study of pragmatics that analyzes about the negative politeness strategies. The aim of this study is to find out the type of negative politeness strategies in movie “Big Hero 6”. The theory used is Levinson (2009). In this research, the researcher applied the qualitative descriptive method. The method of collecting data is observation. The researcher found 20 data that contain negative politeness strategies, the using of be indirect is 1 data, the using of question or hedging is 7 data, the using of minimize imposition 4 data, the using apologize 3 data, the using of give deference 1 data, and the using of plural pronoun is 4 data.
Implementing Web Services using PHP Soap Approach

&lt;p class="0abstract"&gt;Recently, the utilization of IT in the Higher Education institutions has expanded, thus e-Learning must to turn out to be completely embedded into e-Learning and showing practice rather than the traditional approaches to e-Learning. However, this development inside e-Learning frameworks isn't yet completely realized, and the most significant difficulties to this objective are holding students inside instruction and attracting them to take part in Higher Education. One of the methodologies that have been taken to address these difficulties is to utilize the Web services approach to encourage working and participation between Higher Education institutions. Taking account that XML documents are the most commonly applied and successful type of Web services. Being PHP is the best choice for web developers, especially for Web services. This paper will present the proposed approach which aims to expand the current architecture of Web services to meet the technical requirements of the e-Learning framework. It will give an outline of certain strategies that help designers to create SOAP with PHP language. It will portray how to expand PHP Sakai and Moodle to help Web services by utilizing the PHP SOAP method. Besides, it will delineate that this utilization of Web services is a direct advancement of Web programming models, and it will exhibit how PHP can be utilized as a fast and easy development tool for creating them. The spotlight of this paper is to research the expansion of Web services to support PHP Sakai and Moodle by utilizing the PHP SOAP strategy.&lt;/p&gt;
Study of general technical disciplines via interactive audiovisual tools in conditions of informational and educational environment

The study of general technical disciplines for the future engineers training of requires the use of interactive audiovisual tools.Such tools can offer an informational and educational environment.The use of interactive audiovisual tools enhances the quality of theoretical and practical provisions of general technical disciplines.To prepare applicants of higher education in engineering specialties it is expedient to form modern electronic interactive manuals for on disciplines studying in the conditions of the informational and educational environment.Such resources are assistance in mastering both theoretical material and course navigation, which provides interactive electronic learning tools for performing tasks in an informational and educational environment.The tasks for higher education applicants are performed directly in the audience using gadgets or personal computers.The final score is formed from the points obtained in the audience and the rating of higher education applicants during the study in the informational and educational environment.It is expedient to provide information in the informational and educational environment with the help of QR-codes in the methodical literature for studying in the informational and educational environment.General technical disciplines require the mastering of theoretical knowledge, reinforcement by their practical calculations and testing them experimentally.Theoretical positions of general technical disciplines are expedient to learn through lectures with audiovisual accompaniment.Practical tasks are performed on the basis of multimedia materials for practical work, and simplification and automation in performing calculations can be done using online calculators, modeling and design tools.The experimental part in the study of general technical disciplines must be supported by video clips and the implementation of interactive laboratory work.The outlined approach can help in qualitative mastering of educational content in the chosen specialty and reinforcement of engineering skills of higher education applicants.
Towards QoE Optimization in Medical Multimedia Services for Decentralized IoT-based Applications

Fourth industrial revolution ally for elderly patients. As QoS is not the appropriate entity to express the feelings and expectations of the end-users i.e., elderly patients. Therefore, the quality of experience in medical media (QoEMM) services is quite important. This research optimizes the medical media service such as, electrocardiogram (ECG) for the elderly patients by adopting wearable devices with large screen. Due to small size, and resource-constrained nature of those handheld devices it is hard to satisfy the end user's perception while monitoring the elderly emergency patients. Besides, how the elderly patient's QoE during medical media ECG data transmission can be captured, for this purpose first, framework of QoEMM is developed by adopting acquisition time. Second, the relationship between subjective test score (i.e. surveyed data) and objective performance metrics (i.e., energy consumption and entropy) with acquisition time and actual time of ECG service is established. It is revealed through extensive real-time subjective data sets in experimental setup that QoEMM is optimized through portable devices, and correlated with QoS parameters during medical media ECG service to improve the satisfaction level of end-users.
Immediacy Factors as Solutions to Email Satisfactory Communication Among South-East Nigerian Academic Staff: Structural Equation Modeling and Preliminary Findings

Notwithstanding the evidence of utilizing email among Nigerian academic staff as shown in the previous studies, a recent study demonstrated that they witnessed dissatisfactory communication via email as text-based communication medium. Therefore, the aim of our study was to evaluate if immediacy factors might influence their email satisfactory communication since these factors have been ascertained in the past studies as predictors to satisfactory communications in other asynchronous virtual communications. The respondents’ email satisfactory communication levels were further examined in the study for finding if they also contributed to their email dissatisfactory communication. Hence, a quantitative research method was conducted because the study required both descriptive and inferential studies for the aim of inferring the outcomes to the targeted population. Consequently, our key findings showed that more than half of the respondents’ email satisfactory communication level was not a high one. Additionally, our findings showed that the three immediacy factors which comprised prompt feedback, approachability and similar personality had direct effects on email satisfactory communication. However, similar personality factor contributed most to email satisfactory communication. Therefore, we recommend that they should consider these three immediacy factors, especially the similar personality if they aim to achieve email satisfactory communication. Our findings further explicitly contributed knowledge to asynchronous computer-mediated media satisfactory communication. Keywords: Immediacy factors, satisfactory communication, email usage, asynchronous computer-mediated communications, South-East Nigerian academic staff.
Landmark Classification Service Using Convolutional Neural Network and Kubernetes

The use of Deep Learning for the image classification process has developed rapidly, one of which is in a method called Convolutional Neural Network (CNN).One use of the CNN method is to classify images.This study uses the CNN method to classify image datasets that have landmark categories.The results show that each model has an accuracy level with the highest value of 95% and the lowest value of 92%.The method for this research to produce a service that can be used by other services and or can be implemented in other resources so that the classification function can be used or developed.We show that our deployment method has good results seen with ResNet50 Model using 1200 concurrent users which response rates were smaller by 4,92% using autoscaling pods with one minimum pod and 6 maximum pods that had an error value of 26,58% compared with the best result from the other method.
A Chaos based image Encryption Scheme using one Dimensional Exponential Logistic Map.

The widespread use of images in various sectors of life makes its protection increasingly necessary and important. An improvement over encryption and decryption algorithm using exponential logistic chaotic map was proposed. In this work, we adopt an encryption/decryption strategy for colour images using the exponential logistic chaotic map. The proposed encryption/decryption algorithms are implemented in MATLAB for computer simulation. The experimental results indicate that the proposed algorithms can be used successfully to encrypt/decrypt images with secret keys. The performance analysis using histogram uniformity analysis and correlation coefficient show that the algorithms give larger space, quick speed and easy to realize. The encrypted images have good encryption effect and low correlation coefficient rendering it a good candidate for confidential and secure means of transmitting image information in untrusted networks.
Pengujian White Box pada Aplikasi Cash Flow Berbasis Android Menggunakan Teknik Basis Path

An application that has poor quality and defects not only causing additional time of software development process but also can deliver disadvantage to the users of the application. Every application will not be separated from the testing process. The testing process aims to find out errors in the software. One of the methods used is white box testing. White box testing is a testing method at the level of the software flow. To find out whether the Cash Flow application does not have an error it will be tested with a base path technique that starts from making a Flow Graph, Cyclomatic Complexity (CC) and doing a Case unit. The implementation of the white box testing method using the Base path technique in the cash flow application can evaluate the complexity of the program flow and while conducting unit tests it can determine the number of test scenarios to be performed. After doing Cash Flow application testing with no errors, thus all tests were successful. The results of this test can be used as a reference to improve the application as expected.
Іmplementation of Emotional Intelligence Theory in Future Musical Art Teachers Training

The article investigates the ways of implementing emotional intelligence theory in future musical art teachers training.The methodological basis of the study includes synergetic, holistic, and hermeneutic approaches, the application of which allows finding out the ways of the future musical art teacher's emotional intelligence development.It is shown that emotional intelligence is an integral dynamic phenomenon that provides optimistic awareness, understanding, and control of one's emotions and emotions of other people; it also influences the success of communicative interaction.On the basis of the analysis of scientific literature on the issue under investigation and practical experience of training future musical art teachers, the ways of implementing the emotional intelligence theory in the professional preparation of future musical art teachers were determined, namely: activation of students' motivation for emotional interaction in the process of professional preparation; creation of appropriate artisticeducational environment; realization of a practically oriented, personalized, active creative process of development of the future musical art teachers' emotional intelligence through introduction of training technologies; involving students in constructive activities through joint events, game teaching methods, dramatization, etc.; learning self-talk skills, internal dialogue and self-affirmation; improving the effectiveness of artistic-pedagogical communication and professional training of the future musical art teachers; carrying out research activities.It is proved that the use of the provisions of the multiple intelligences theory in HEI for the development of emotional intelligence provides opportunities to students' self-cognition; better understanding of students' talents and abilities by teachers; stimulating creation of innovative teaching methods and forms; involving students in the creative learning process, taking into account the natural capabilities of all types of intelligence.
Hardware Acceleration of Sparse Support Vector Machines for Edge Computing

In this paper, a hardware accelerator for sparse support vector machines (SVM) is proposed. We believe that the proposed accelerator is the first accelerator of this kind. The accelerator is designed for use in field programmable gate arrays (FPGA) systems. Additionally, a novel algorithm for the pruning of SVM models is developed. The pruned SVM model has a smaller memory footprint and can be processed faster compared to dense SVM models. In the systems with memory throughput, compute or power constraints, such as edge computing, this can be a big advantage. The experiments on several standard datasets are conducted, which aim is to compare the efficiency of the proposed architecture and the developed algorithm to the existing solutions. The results of the experiments reveal that the proposed hardware architecture and SVM pruning algorithm has superior characteristics in comparison to the previous work in the field. A memory reduction from 3 % to 85 % is achieved, with a speed-up in a range from 1.17 to 7.92.
ANALISIS PEMAHAMAN KONSEP IPS MATERI KEGIATAN EKONOMI MENGGUNAKAN VIDEO PEMBELAJARAN IPS SISTEM DARING DI KELAS IV.3 SDN PAKUJAJAR CBM

The purpose of this study is to describe the results of the results of the analysis of the ability to understand social science concepts in the material "economic activity" when using video learning with an online system in class IV.3 SDN Pakujajar CBM. The research method used is descriptive qualitative method. Data collection techniques used were interviews and documentation. The writer acts as an instrument of data collection.Data analysis techniques used are according to Miles and Huberman, namely data reduction, data display, and conclusion drawing / verification. The research subjects used were grade IV.3 students in the 2019/2020 school year. The number of students is 25 people. The results showed that the ability to understand social science concepts in economic activity material, 7 students got the highest score, while 1 student got a grade less than KKM. All indicators can be mastered by students, but there are several categories, namely high to very high. The very high category can be combated as much as 96% in the exemplary indicator.
Data Anonymization for Big Crowdsourcing Data

In traditional database systems, data anonymization has been extensively studied, it provides an effective solution for data privacy preservation, and multidimensional anonymization scheme among them is widely used. However, without delicate parameter settings, these technologies may cause uncontrollable information loss and decrease the accuracy of data analytic tasks. Furthermore, crowdsourcing data is usually huge in amount and must be distributed stored in clouds, which makes the conventional data anonymization technologies not applicable. In this paper, we propose a framework that uses MapReduce to anonymize large-scale data before disseminating them to human workers. In order to guarantee the number and distribution of data records to be similar in all nodes, our framework first redistributes the original data to all participating nodes. Then a heuristic two-phase anonymization schema, which can be seamlessly integrated into the framework, is proposed. Experimental results show that with the same objective of privacy, our approach is scalable for large-scale data and can improve the average accuracy of human worker's analytic tasks.
Copyright and Digital Collections: A Data-Driven Roadmap for Rights Statement Success

An earlier version of this manuscript was presented by the authors at the biennial conference of the Association of College and Research Libraries, April 13, 2019. The authors wish to acknowledge the Research and Publication Committee of the University of Illinois at Urbana-Champaign Library, which provided support for the completion of this research. We would also like to thank Janet Swatscheno, the Digital Publishing Librarian at the University of Illinois Chicago, for her helpful comments on an earlier draft of this article. This article summarizes the results of interviews with Digital Public Library of America (DPLA) service hub participants to determine whether and how standardized rights metadata is included in their digital collections. Providing accurate standardized rights metadata is crucial to communicating with patrons regarding how they can use objects in digital collections. Results from the interviews reveal key findings on effective rights statement implementation techniques as well as common tools used by librarians when applying rights statements to digital collections.