Reviewerly/exHarmony huggingface dataset:
DATA STORING AND RETRIEVAL METHOD IN BIG DATA USING FUZZY BASED SCALABLE CLUSTERING ALGORITHMS

A massive volume of digital data holding valuable information, called Big Data, is produced each generation. To process and excavate such valuable information, clustering is commonly used as a data investigation technique. A huge amount of Big Data diagnostics contexts have been established to measure the clustering procedures used for big data analysis. There exists one and only framework called Fuzzy based mechanism which actually fits in for iterative method by associate in storage divisions and accessible. The proposed algorithm is motivated towards the design and implementation of fuzzy based clustering algorithms on big data, which could be present for clustering huge datasets due to their low computational necessities. In this paper, we propose Random Data Storing with Optimization Fuzzy Logic algorithm (RDS-FLA) applied on cluster data to handle the tasks that are connected with big data clustering. Experimental trainings data taking place several big datasets have been showed. The performance of RDS-FLA is tried in evaluation with the proposed scalable form of the temporal fuzzy and Random data storing that is implemented on the big data cluster. The computation outcomes are recounted in terms of time and space complexity, run time and measure of clustering quality, showing that RDS-FLA is able to run in much less time without compromising the clustering quality. Thus, the algorithm proposed alleviates the processing time and increases the security of storage data effectively. Advantages such as cost optimization and efficiency in data security can be identified from the experimental results of proposed algorithm.
Design and evaluation of a digitally active drum

Abstract Despite the ever growing variety and popularity of commercially available electronic percussion (EP) instruments, there are still a significant number of active musicians who prefer to use acoustic drums. Digitally active drum (DAD) is an enhanced snare drum that provides sonic capabilities associated with digital musical instruments in the form of a traditional acoustic drum allowing full use of acoustic drumming gesture vocabulary. By using an in-built loud speaker and tactile sound transducers system, a Bela Cape and Beagle Bone Black, near field photoelectric sensors and a synthesis and effects patch built in Pure Data (PD), a prototype of a hybrid acoustic - electronic instrument has been made. This prototype has been evaluated by five expert drummers and two co-performers in both group and solo settings in order to determine its effectiveness and potential role in professional music making.
Classification of Industrial Espionage Cases and Countermeasures

Modern national power depends on how many core technologies of high economic value the nation possesses. Companies are investing in R&D to secure competitiveness in their fields but efforts to counter industrial espionage does not match these actions resulting in serious monetary damages. Industrial espionage cases regarding intellectual property is on the rise due to this indifferent attitude of companies. Therefore, this study focuses on industrial espionage cases cause and course of outflow in the perspective of statistics and seek countermeasures by analyzing the trend of industrial espionage activities. This study classifies the cases in 5 different ways including the subject of industrial espionage, nation, means, and technology classes. After the analysis, the study presents countermeasures according to 'Guidelines to Secure Industrial Technology', 'Guidelines to Secure Small and Medium Sized Enterprises Industrial Technologies' by Korea Association of Industrial Technology Security and Ministry of SME(Small and Medium Enterprise)s and Startups.
Gabriella: An Online System for Real-Time Activity Detection in Untrimmed Surveillance Videos

Activity detection in security videos is a difficult problem due to multiple factors such as large field of view, presence of multiple activities, varying scales and viewpoints, and its untrimmed nature. The existing research in activity detection is mainly focused on datasets, such as UCF-101, JHMDB, THUMOS, and AVA, which partially address these issues. The requirement of processing the security videos in real-time makes this even more challenging. In this work we propose Gabriella, a real-time online system to perform activity detection on untrimmed security videos. The proposed method consists of three stages: tubelet extraction, activity classification, and online tubelet merging. For tubelet extraction, we propose a localization network which takes a video clip as input and spatio-temporally detects potential foreground regions at multiple scales to generate action tubelets. We propose a novel Patch-Dice loss to handle large variations in actor size. Our online processing of videos at a clip level drastically reduces the computation time in detecting activities. The detected tubelets are assigned activity class scores by the classification network and merged together using our proposed Tubelet-Merge Action-Split (TMAS) algorithm to form the final action detections. The TMAS algorithm efficiently connects the tubelets in an online fashion to generate action detections which are robust against varying length activities. We perform our experiments on the VIRAT and MEVA (Multiview Extended Video with Activities) datasets and demonstrate the effectiveness of the proposed approach in terms of speed (~100 fps) and performance with state-of-the-art results. The code and models will be made publicly available.
LibGuides: Map Collections at USU Libraries: Finding Maps

Looking for maps in USU Libraries collections? See all of your options in one place with this guide.
How the current media strategy of the National Paralympic Committee of Azerbaijan provides an opportunity to expand audience and influence prior to the Tokyo 2020 Paralympic Games

With the preparations for the Tokyo 2020 Paralympic Games already underway, the media strategy of the Azerbaijan Paralympic Committee is facing a critical test. The objective of the Paralympic Committee of Azerbaijan is not only to promote and channel the efforts of the country’s Paralympic athletes, but to promote a more inclusive civil society. The run-up to the Paralympic Games and during the competition itself represents a major opportunity for the Committee to expand its reach and audience, attracting new supporters, sponsors and potential athletes and helping to inspire those facing physical challenges in Azerbaijan. But are the media strategy and current channels of the Paralympic Committee ready to take on this challenge? This research aims to assess the current strength of the Paralympic Committee’s media strategy, through comparison with Paralympic Committee activities in other countries, and through analysis of their current platforms using industry standard benchmarking. It goes on to assess the potential for further development of the Paralympic Committee’s media framework, both through improvement of existing channels and through innovation. My research strongly suggests that there is potential for improvement and an opportunity to expand the audience for Paralympic-related news and information. My research will be made available to the Paralympic Committee, in order to support and inform their media strategy. Further research and planning will be conducted into the potential to launch innovative new channels, as part of my Master’s programme studies and as part of a commitment to support the ideals and objectives of the Paralympic Committee of Azerbaijan.
Design and test water intake monitor to improve human’s well-being

Water is a substance that the human body needs in order to survive. Drinking the right amount of water has many health benefits, including maximum physical performance, high energy levels, and improved brain function. Dehydration occurs when the body uses or loses more fluid than it takes in. When dehydration happens, the body doesn’t have enough fluids in it to carry out its normal functions. In older adults, dehydration is the most common disorder that can occur. As adults get older, the body’s fluid reserve becomes smaller, and the ability to process and conserve water is reduced. We have designed a sensor to track to the amount of water put into the body. This monitor will help seniors, especially those in a nursing home, to track their daily water intake. The sensor works with other personalized data to create a dashboard to their medical provider for better health care. There are still some limitations of the sensor. We will continue to improve the accuracy of measurement and the material we used.
Pedagogical Approach to Effective Cybersecurity Teaching.

Initial research ruled out many factors that were thought may correlate to student academic performance. Finally, a strong correlation was found between their academic performance and their motivation. Following on from this research teaching practice was restructured to improve student motivation, engagement, and interest in cybersecurity by contextualizing teaching material with current real-world scenarios. This restructuring led to a very significant improvement in student academic performance, engagement and interest in cybersecurity. Students were found to attend more of their lectures and practical sessions and that this had a strong positive correlation with their academic performance.
All you need is a second look: Towards Tighter Arbitrary shape text detection

Deep learning-based scene text detection methods have progressed substantially over the past years. However, there remain several problems to be solved. Generally, long curve text instances tend to be fragmented because of the limited receptive field size of CNN. Besides, simple representations using rectangle or quadrangle bounding boxes fall short when dealing with more challenging arbitrary-shaped texts. In addition, the scale of text instances varies greatly which leads to the difficulty of accurate prediction through a single segmentation network. To address these problems, we innovatively propose a two-stage segmentation based arbitrary text detector named \textit{NASK} (\textbf{N}eed \textbf{A} \textbf{S}econd loo\textbf{K}). Specifically, \textit{NASK} consists of a Text Instance Segmentation network namely \textit{TIS} (\(1^{st}\) stage), a Text RoI Pooling module and a Fiducial pOint eXpression module termed as \textit{FOX} (\(2^{nd}\) stage). Firstly, \textit{TIS} conducts instance segmentation to obtain rectangle text proposals with a proposed Group Spatial and Channel Attention module (\textit{GSCA}) to augment the feature expression. Then, Text RoI Pooling transforms these rectangles to the fixed size. Finally, \textit{FOX} is introduced to reconstruct text instances with a more tighter representation using the predicted geometrical attributes including text center line, text line orientation, character scale and character orientation. Experimental results on two public benchmarks including \textit{Total-Text} and \textit{SCUT-CTW1500} have demonstrated that the proposed \textit{NASK} achieves state-of-the-art results.
Scientific And Educational Technologies In Human Capital Formation

The article deals with a constructive role of socio-humanitarian and philosophical knowledge in the system of natural science structures. It is proved that the relevance of socio-humanities and philosophy is a response to the challenges of the modern technology-based civilization, where exact and natural sciences call for revival of a philosophic component in the education system and science. In the article, the main cause-and-effect relations that have resulted for modern societies in the demand for revival of philosophic and socio-humanitarian knowledge in science and education are revealed. A new paradigm for the development of philosophic and socio-humanitarian knowledge is presented.&#x0D; The authors present the implementation results of a new interdisciplinary dialogue in the system of socio-humanities and natural sciences within the Zaporizhzhia State Medical University, where the Department of Social Studies has adapted and implemented a number of projects in this area. One of which is the School for Young Lecturers – project in the framework of practice-oriented education&#x0D; The article emphasizes that the return of social science to the higher education system and its role in science must be considered as a complex, multi-level process that should be studied and comprehended for its optimal implementation.
The Impact of Knowledge Management Uses on Total Quality Management Practices: An Empirical Study on Commercial Banks of Jordan

This study tested the impact of knowledge management uses on total quality management practices in commercial banks of Jordan. A quantitative research design, using regression analysis was applied in this study and a total of 250 valid returns were obtained through a questionnaire distributed to the employees of commercial banks in Jordan. Knowledge management uses was adopted as an independent variable with four subgroups: knowledge acquisition, knowledge storage, knowledge transfer and knowledge application. Total quality management practices were adopted as dependent variable with five subgroups: top management support, employee's involvement, continuous improvement, customer focus, and data driven decision management. The results show that three of the knowledge management dimensions (i.e. knowledge acquisition, knowledge storage, and knowledge transfer) significantly affects total quality management practices. However, knowledge application showed insignificant effect. The theoretical and practical implications of this study are discussed at the end of this paper.
Data Mining on Cloud-Based Big Data

Large and complex data sets emerged pervasively poses significant challenges to cloud computing. Both structured and unstructured data have grown exponentially in a cloud. A key challenge in big data is to handle the unstructured data in a cloud. To overcome this problem, we use Hadoop MapReduce algorithms to convert unstructured data to structured data by splitting the input data set into independent chunks, which are then processed by the map tasks in a completely parallel manner for large data sets. After that, we use the Data Mining incremental decision tree algorithm for efficiently accessing the big data. In this way, we can access cloud data accurately and easily.
Application of Power-Law Frequency Fractal Model for Recognition of Vertical Cu Distribution in Milloieh Porphyry Deposit, SE Iran

Identification of the vertical and horizontal distributions for elemental grades is of an important sign in different mineral exploration stages. The main aim of this work is to determine the vertical distribution directional properties of Cu values in the Milloieh Cu porphyry deposit, Kerman (SE Iran) using the power-law frequency fractal model. This work is carried out based on four mineralized boreholes. The Cu grade vertical distribution in mineralized boreholes indicates a positively skewed distribution in the former and multi-modal distribution in the latter types. The power-law frequency analysis in nature represents that the Cu values in four mineralized boreholes are bifractal. The two sections of these graphs outline a break point of about 0.5-1% for Cu values and fractal dimension range of 1.70-4.97 in the mineralized boreholes.
The Duration of Pauses between Phrases in Reading Language

The aim of this research is to determine the duration of the pauses between paragraphs and sentences in reading language and their connection with the length and reading speed of said language units. The research material consists of 48 sound recordings (eight Lithuanian speakers read six texts representing different functional styles). The results show that all readers usually pause between paragraphs and the duration of those pauses depend on the reading speed: faster readers pause for approximately 400–1340 ms, while slower readers pause for 750–1800 ms. Pauses are the shortest after short paragraphs and they are 1.2 times longer after longer paragraphs. All the readers usually pause between sentences as well. Faster readers on average pause for 200–980 ms, slower readers pause for 340–1360 ms. The longer the sentence, the longer the pause after that sentence (up to 1.4 times). However, the pause can be the same duration after both long and medium length sentences.
WORLD EXPERIENCE: COMMERCIAL BANK CREDIT AND ECONOMIC GROWTH RELATIONSHIP

This research focuses on the problem of large scale disproportion of success in the development of the banking sector and mostly unsuccessful development of the real sector of the economy. It should be noted that this disproportion is a subject of consideration in contemporary economic literature and our research is an attempt to broaden the issue and share ideas inside the international scientific circles. The main problem in the research is the impact of the banking sector's credit portfolio and the functioning of credit markets on the economic growth of the country. In this regard, it is very important to identify, study the macroeconomic stabilization and accelerated economic growth of the country and analyse the impact mechanisms of the credit market factors on economic growth. The conclusion that combines many of the research and opinions given in the survey can be as follows: From the economic point of view, the main function of banks is to increase the financing/lending of funds as the core point to increase investments in the economy. Thus, the development of the country in economic terms depends on the increase of investments. At present, it is in the hands of the banking sector whether to lead us to economic immobility or to accelerate the country's economic development through efficient allocation of resources.
Sampling and Sampling Distributions

This chapter introduces the notion of taking a random sample from a population and considers how one may use sample statistics to infer things about possibly unknown population parameters. Classical results about the sample mean and sample variance are stated, and here famous continuous distributions which are the cornerstone for statistical inference are described: Normal, Student’s t, the chi-squared, and F. One of the most important results in statistical inference, the Central Limit Theorem, is discussed.
SUBSTANTIATION OF THE METHODOLOGICAL EXPEDIENCY TO USE THE METHOD OF WRITING ESSAYS ON SOCIAL AND PEDAGOGICAL TOPICS

&#x0D; &#x0D; &#x0D; &#x0D; The article presents an attempt to provide a comprehensive substantiation of the feasibility of using the method of writing an essay on social and pedagogical topics during the teacher training process. Based on the interpretation of the method essence, its functional purpose in philosophical and linguistic literature as well as works on literary studies, they determine the adaptation foundations regarding the specific features of the effective use of the essay method in the educational process, pedagogy as an academic discipline. Specific examples are used to demonstrate the priorities of the essay method when developing social competence in particular and the social reflection of the future teacher in general. They mention the strengthening of the roles of the student’s activities related to self-education and self-assessment, development of their creative reflective thinking, and the strengthened ability to make effective decisions regarding a burning problem of both professional and social significance.&#x0D; &#x0D; &#x0D; &#x0D;
‘한국어교육론’ 교과목의 플립러닝 수업 설계 연구 -Bloom의 신 교육목표분류학에 기반하여-

This study illustrates an instructional model for flipped learning through an example of the ‘Introduction to Korean Language Education’ course, an introductory undergraduate course in KSL(Korean as a Second Language). Flipped learning is an instructional model that allows students to engage in active learning by creating a meaningful and motivating context for learning. The model incorporates a variety of pre-class, in-class, and post-class activities which help learners to construct/reconstruct their knowledge and develop critical thinking skills. This study demonstrates how the knowledge and cognitive process dimensions of the revised Bloom’s Taxonomy can be applied to classroom teaching and learning through an inductive approach. This study proves that flipped learning can promote students’ higher order thinking ability and can be easily adaptable to various levels and dimensions of knowledge. Based on the experience of designing and implementing a flipped learning model, the author offers a few pedagogical suggestions. First, just as instructors may feel burdened with creating various learning tasks and activities, learners can feel overwhelmed with a number of student-centered activities. The findings of this study indicate that in terms of course length, seven to eight weeks of flipped learning will be appropriate for effective learning. Second, in order to implement interactive tasks and activities as well as offer individualized feedback, it will be ideal to limit the number of students to less than 30. Finally, securing classrooms that can accommodate various group activities is essential for flipped classroom instruction. (Kyung Hee University)
Games, Puzzles and Treewidth

We discuss some results on the complexity of games and puzzles. In particular, we focus on the relationship between bounded treewidth and the (in-)tractability of games and puzzles in which graphs play a role. We discuss some general methods which are good starting points for finding complexity proofs for games and puzzles.
Special datasets for training learning algorithms

Successful performance of machine learning approaches for object classification requires training with data sets that are good representations of actual field data. Most open source image databases, while large in size, are not representative of the type of scenes encountered by Army ground missions. The CCDC Army Research Laboratory hosts datasets, some collected recently, and some a few years ago that focus on Army scenarios and are thus an appropriate source of training data for defense applications. This paper presents examples of several of these datasets along with conditions of their availability to external research collaborators.
Le metafore nella letteratura italiana della migrazione.Studi e riflessioni

In this brief essay, I go through the different steps of a linguistic research Ihave conducted about metaphors in Italian novels by non-native-italophonewriters. The focus of the research was to identify the path, if any, of the metaphorsand images transfer from one’s conceptual/cultural native languageto the language chosen for one’s artistic literal purpose. My former linguisticanalysis passed through formal considerations about metaphors: how one canrecognize them within a sentence, both by means of their patterned syntagmaand by means of their figurative significance. Now, it urges to return onthe obtained results and start new cultural reflections about them. Seen at adistance, actually, they are revealing unforeseeable aspects that, through andwith language, contribute to describe a profound evolution in the way MigrationsLiterature, and migration itself, is conceived and described, and moreover,how much it seems that the starting point of scholars studying this phenomenonmay have changed.