Reviewerly/exHarmony huggingface dataset:
A Dense Optical Flow Field Estimation with Variational Refinement

Optical flow has long been a focus of research study in computer vision community. Researchers have established extensive work to solve the optical flow estimation. Among the published works, a notable work using variational energy minimization has been a baseline of optical flow estimation for a long time. Variational optical flow optimization solves an approximate global minimum in a well-defined nonlinear Markov Energy formulation. It works by first linearizing the energy model and uses a numerical method specifically successive over-relaxation (SOR) method to solve the resulting linear model. An initialization scheme is required for optical flow field in this iterative optimization method. In the original work, a zero initialization is proposed and it works well on the various environments with photometric and geometric distortion. In this work, we have experimented with different flow field initialization scheme under various environment setting. We found out that variational refinement with a good initial flow estimate using state-of-art optical flow algorithms can further improve its accuracy performance.
Feature Fusion for Image Retrieval using Image Processing.

Image processing and computer vision uses Content-based image retrieval (CBIR) function to solve the issue of image retrieval, which means, solving the issue of image searching in expansive databases. The actual data of the image will be evaluated when a search is performed that refers to content-based. The term content can be any attribute of an image like colour-shade, various symbols or shapes, sizes, or any other data. There are various approaches for image retrieval but the most prominent are by comparing the main image with the subsets of the relatable images whether it matches or not and the other one is by using a matching descriptor for the image. One of the main trouble for huge amount of CBIR is the representation of an image. When a given image is worked upon it is divided into number of attributes in which some are the primary ones and others are the secondary ones. These attributes are checked with the local and MPEG-7 descriptors. All this is then mapped in a single vector which is the same images but in compact form to save the space. Principle Component Analysis (PCA) is used lessen the attribute size. To store the attribute data in similar clusters and to train them to give the correct output the study also uses k-means clustering algorithm. Hence, the proposed system deals with the image retrieval using various algorithms and methods.
Line Segmentation Challenges in Tamil Language Palm Leaf Manuscripts

The process of an Optical Character Recognition (OCR) for ancient hand written documents or palm leaf manuscripts is done by means of four phases. The four phases are ‘line segmentation’, ‘word segmentation’, ‘character segmentation’, and ‘character recognition’. The colour image of palm leaf manuscripts are changed into binary images by using various pre-processing methods. The first phase of an OCR might break through the hurdles of touching lines and overlapping lines. The character recognition becomes futile when the line segmentation is erroneous. In Tamil language palm leaf manuscript recognition, there are only a handful of line segmentation methods. Moreover, the available methods are not viable to meet the required standards. This article is proposed to fill the lacuna in terms of the methods necessary for line segmentation in Tamil language document analysis. The method proposed compares its efficiency with the line segmentation algorithms work on binary images such as the Adaptive Partial Projection (APP) and A* Path Planning (A*PP). The tools and criteria of evaluation metrics are measured from ICDAR 2013 Handwriting Segmentation Contest.
Techniques of Big Data Text Summarization

In the web industry 4.0, big data are playing a key role in the organizations of their digital transformation journey. Data has also changed intensely in recent years, in volume, variety and velocity. Its fast development attributed to the extensive digitization of business progressions globally. In simple term, data has turn into the new currency of business and its further quick growth will be key transformation and growth of organizations globally. Vast amount of online information, available in healthcare, social media websites, e-commerce web pages, e-books, legal domain, e-news, etc. has made text processing a vital extent of research. The paper starts with introduction about the evolution of web industry 4.0 and digitalization. Followed by the introduction, the paper discusses about big data and text summarization techniques. Further, it describes the literature of text mining that have taken in the recent years. The main objective of this paper is to discuss about the big data text summarization issues and challenges. The paper starts with general introduction of big data and text mining and text summarization. Further it describes recent advances in big data text summarization, and then delve into extraction and abstraction-based text summarization. Finally, the paper concludes with some future research directions.
Cryptocurrency as a Property

The debate at this level needs to be centred on the determination of whether cryptocurrencies should be classified as a currency or as an intangible property. Although we have a view on this point, there are differing implications that a classification will engender. Where it is decided that cryptocurrencies be classified as a currency, CBN will rightly exercise regulatory control, otherwise, not. There are also tax considerations that arise from a classification, either way. For instance, if bitcoin or other cryptocurrencies is considered a property, this classification may trigger sales tax obligations. Also, a classification as an intangible property will take bitcoins (and other cryptocurrencies) out of the Exclusive Legislative List in the Nigerian constitution– not being a legal tender– and provide state governments with the legislative competence to regulate cryptocurrencies
Study on Physical Movement Education Support Method in Manufacturing Skills

In this paper, I proposed an educational support design method that enables learners to agentic aware skill information when learning skills that involve physical movements. First, skill information is collected by the skill information structuring method proposed by the author, and structuring is performed in consideration of the effect on the quality of the deliverable. Next, I proposed a new method for designing a learning program by selecting presentation information and evaluation items according to the learning process of physical skills. Here, the presentation information and the evaluation information are fed back so that the learner can agentic aware the important physical control factors and somatosensory factors in the skill movement. In the future, I will develop a system for extracting information and creating learning programs, and study learning efficiency and learning process.
Customize Your Gameplay: Minecraft Hardware Programming

This chapter will look at how electronics can be integrated with other programs through an API (application programming interface). It will also create a game console–type device complete with joystick and arcade buttons. This is based around the API for Minecraft Raspberry Pi edition, which is available for free for the Raspberry Pi.
Students' characteristics in programming learning and the design of a mobile learning platform

We studied the correlations between novice students' performance in an introductory programming course and their learning characteristics and styles as well as their motivations toward this difficult area. Based on the findings, we then provided a conceptual design of a mobile learning platform for enhancing their performance, using the most prevalent messaging and social media applications (APPs) among the students. The study took place in two different academic years for students taking introductory programming courses at Macao Polytechnic Institute in Macao and the University of Coimbra in Portugal. We compared the results of the two samples and found that although we could not establish correlations in many cases, we were able to get some insights on some context and teaching aspects that might be improved. The most important factor to improve the students' performance in their first programming course is to enhance their confidence and motivation in a visual learning environment.
Coherence of critical reading skills and teacher training development

The study presents critical reading as a specific type of learning activity in education. The focus of the research is on the content and structure of critical reading process aimed at the development of critical reading skills as one of the objectives of professional training in pedagogical universities with much attention paid to the ways students and teachers conceptualize this phenomenon. The authors advance some ideas concerning the scope of critical reading skills as part of teacher’ professional competence.
Natural Language Processing Improves Detection of Non-Severe Hypoglycemia in Medical Records versus Coding Alone in Patients with Type 2 Diabetes but does not Improve Prediction of Severe Hypoglycemia Events: An Analysis Using the Electronic Medical Record in a Large Health System

Objective: To determine if natural language processing (NLP) improves detection of non-severe hypoglycemia (NSH) in patients with type 2 diabetes and no NSH documentation by diagnosis codes, and to measure if NLP detection improves the prediction of future severe hypoglycemia (SH). &lt;p&gt;Research Design and Methods: From 2005-2017, we identified NSH events by diagnosis codes and NLP. We then built an SH prediction model. &lt;/p&gt; &lt;p&gt;Results: There were 204,517 patients with type 2 diabetes and no diagnosis codes for NSH. Evidence of of NSH was found in 7035 (3.4%) using NLP. We reviewed 1200 of the NLP-detected NSH notes and confirmed 93% to have NSH. The SH prediction model (C-statistic 0.806) showed increased risk with NSH (Hazard Ratio=4.44, p&lt;0.001). However the model with NLP did not improve SH prediction compared to diagnosis code-only NSH. &lt;/p&gt; &lt;p&gt;Conclusions: Detection of NSH improved with NLP in patients with type 2 diabetes without improving SH prediction. &lt;/p&gt;
3D (.Obj) Image Watermarking and Key Generation Using Dwt Algorithm

Digital media like images ,3D models audio and video can be used to embed signals in digital form. This process is popularly known as Digital Watermarking.The digital watermarking process is done by different methodologies such as steganography and by cryptography. The steganography method is used to hide the data and the cryptography method is used to encrypt the data into desired format. In this paper we proposed the method of cryptography and DWT (Discrete Wavelet Transform) algorithm for hiding the data and to generate a secret key for the data transmission. The data is embedded in a 3D real time object (.obj). The frequency and energy of the image pixel is calculated by DWT algorithm and by doing XOR operation the secret key will be generated by cryptography method. The 3D image is divided by vertical splicing technique. The data is embedded into an image in the form of binary data as 0’s and 1’s.
Abstracts of the 33&lt;sup&gt;rd&lt;/sup&gt; International Meeting of Physical Therapy Science in Ohtawara

Relationship between maximum calf circumference
Persepsi Publik Terhadap Kinerja Pemerintah Kota Pekanbaru dalam Pengendalian Banjir Tahun 2015-2017

The Pekanbaru City has a densely populated population of more than one million. Along with the development of Pekanbaru City into a Metropolitan City, it is inseparable from various problems that arise, namely the problem of flooding. The problem of flooding is a problem that does not resolve every year. This was caused by the development of Pekanbaru City which was not followed by adequate flood control infrastructure systems. In this case, of course, the public spotlight on the performance of the government in overcoming flood problems in the city of Pekanbaru. The formulation of the problem in this study is What is the public perception of the performance of the Pekanbaru City Government in 2015-2017 Flood Control?This study aims to determine how public perceptions of the performance of the Pekanbaru City Government in flood control in 2015-2017 are seen from aspects: (1) Productivity, (2) Service Quality, (3) Responsiveness, (4) Responsibility, and (5) Accountability. This research is a descriptive study using the Mixed Method approach. The data collection technique in this study is to use a survey technique by taking a sample of 100 people from one population using a questionnaire as a means of collecting basic data and using interview techniques with a total of 10 informants.Data analysis used for quantitative methods is quantitative analysis and analysis for qualitative methods using qualitative analysis, and finally is analyzing data combined with qualitative analysis and quantitative analysis.The results of the study concluded that public perception regarding the performance of the Pekanbaru City Government in 2015-2017 flood control was still not good. This is shown from the results of the average value of each indicator (productivity, service quality, responsiveness, responsibility, and accountability) which is equal to 1.95 which is in the range of 1.76 - 2.50 which shows unfavorable criteria. In this case the public considers that the Pekanbaru City Government has not been able to optimize the implementation of flood control in Pekanbaru City.
Know What's Key to Story Placement

Nonprofit Communications ReportVolume 19, Issue 9 p. 5-5 Media Relations Know What's Key to Story Placement First published: 05 August 2021 https://doi.org/10.1002/npcr.31783Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume19, Issue9September 2021Pages 5-5 RelatedInformation
PCA + LDA Fuzzy Based Model for Emotional Nature Recognition of Human Video

Human expresses their emotions by means of verbal and nonverbal communication. Nonverbal communications are done mainly using facial expression. This paper aims to recognize human emotion using nonverbal communication of human facial expressions. Different mathematical techniques like: principle component analysis (PCA), linear discriminate analysis (LDA) and independent component analysis (ICA) are widely used for human facial expression recognition. This paper applied fusion of PCA and LDA based model for facial video emotion recognition with neural network (NN), fuzzy approach and Ekman’s proposed concept of action units of faces. Moreover, results obtained in linguistic form using action units with fuzzy approach on unknwn individual persons for identification of nature of input video and compare with the actual data to validate the model. This paper concludes that developed approach provides 99% accuracy for human facial expression recognition and identification of nature of input video.
MAVIG Portegra Overhead Counterpoise

Biomedical Safety & Standards 49(5):p 35, March 15, 2019. | DOI: 10.1097/01.BMSAS.0000553906.77162.78
Adoption of Blockchain to build a Cryptocurrency for Ledger Systems

The idea of the cryptocurrency was to decentralize the currency system by establishing transactions over distributed peer to peer network [1]. The technology of Blockchain was adopted to achieve this motive. The term blockchain comes from the idea of list of blocks, growing continuously over time wherein every block carries the data relating to the transactions and data regarding the cryptographical linkage using secure hash algorithms and the protocols [2]. Through this paper, we have shown the implementation of the blockchain technology so as to build the cryptocurrency. While building up the cryptocurrency, called the ‘SantCoin’, the idea about how this technology can revolutionize the traditional existing ledger systems can be upgraded so as to implement secure means of transactions over a distributed network. This implementation work suggests the use of technology in almost every governing body so that they can secure themselves and limit the dependency on human resource to do their central authoritative work [3].
Features Selection Based ABC-SVM and PSO-SVM in Classification Problem

Feature selection can be used to improve the performance of classification algorithms. This study aims to use algorithms for feature selection in classification problems. The method in feature selection use to the Artificial Bee Colony (ABC) algorithm and Particle Swarm Optimization (PSO) based on Support Vector Machine (SVM). The ABC-SVM algorithm functions as a method of feature selection to choose the optimal subset according to the objectives set to provide the results of the classification. Then, the PSO-SVM as a comparison method in other feature selection. The results of the classification conducted by PSO-SVM with the vowel dataset is good classification (AUC 0.873), when compared with the ABC-SVM with the classification result is superior (AUC 0.996). The results of the Precision Recall and F-Measure calculations on the PSO-VSM algorithm have good classification results for sonar and wavefrom data sets. Meanwhile, the results of tests conducted by ABC-SVM get superior value from the classifier quality efficiency in the vowel data set.
Science

Stoppard's theatre regularly engages with science, both in works that specifically deal with issues like chaos theory, quantum physics, and consciousness, and in those which more generally raise questions about the limits of human abilities to understand and control the natural world.
Hierarchical text classification using Relative Inverse Document Frequency

Automatic hierarchical text classification has been a challenging and in-needed task with an increasing of hierarchical taxonomy from the booming of knowledge organization. The hierarchical structure identifies the relationships of dependence between different categories in which can be overlapped of generalized and specific concepts within the tree. This paper presents the use of frequency of the occurring term in related categories among the hierarchical tree to help in document classification. The four extended term weighting of Relative Inverse Document Frequency (IDFr) including its located category, its parent category, its sibling categories and its child categories are exploited to generate a classifier model using centroid-based technique. From the experiment on hierarchical text classification of Thai documents, the IDFr achieved the best accuracy and F-measure as 53.65% and 50.80% in Top-n features set from family-based evaluation in which are higher than TF-IDF for 2.35% and 1.15% in the same settings, respectively.
Perancangan Sistem Layanan Informasi Akademik Berbasis Web pada Fakultas Teknik Universitas Bhayangkara Jakarta Raya

Academic Information Services at a Faculty is very important to provide and provide information needed by students. But this is not the case, because the faculty of engineering still does not provide services in providing accurate information due to the absence of an information system that facilitates all the requirements for services to students. Therefore, the need for designing this information system is expected to be a tool for the faculty in providing information and also makes it easier for students to get access to information anywhere and anytime without coming to campus to find out the latest information. With a web-based application that can be accessed by mobile devices and others, the information that will be obtained for students can be received quickly, precisely and accurately because the management of the information system is managed directly by the faculty. Thus, students get information on the Faculty of Engineering's academic information services without having to first come to campus, by using a web-based application as an information system that is easily accessed
Realization of Parallelism in a Sequential Legacy ‘C’ Program

In the present era of high speed computation with the multicore and other parallel processors in the computational field, there are still some organizations which rely on their old software systems developed years ago, which over the time have been subjected to continous development by different developers. Even though these softwares persist with the old and little in use technology, they still work to satisfy the operational demands of the organizations and have kept them going in the competetive industry. These systems which have with time grown into legacy, embed the major business functionalities of the organization, which is but effort of years. Hence a methodology is required to rebuild the legacy system to make them suitable for execution on to the present computation systems. The paper discusses a research work, wherein work is done to realize points of latent parallelism in a sequentially executing legacy ‘C’ program which is initially restructured and the design information abstracted. A technique using finite state machine is proposed to identify tasks, events, processes and jobs in the program, which helps to locate functionally independent computational units in the program. Furthur using the slicing technique, slicing is performed to extract out the appropriate lines of codes defined by the slicing criteria, which assembled together form a functionality that can be executed in parallel with other extracted functional modules or computational units on any parallel computational platform.
A novel imbalanced data classification algorithm based on fuzzy rule

The classification of imbalanced data can increase the comprehensibility and expansibility of data and improve the efficiency of data classification. The accuracy of classification is poor when the data is classified by the current method for imbalanced data analysis of big data. To this end, this paper presents an imbalanced data classification algorithm based on fuzzy rule. The algorithm firstly collects the imbalanced data, selects the features of the imbalanced data, and optimises the imbalanced data classification algorithm by using the fuzzy rule classification algorithm. The experimental results show that when the classifier maintains a certain size of the weak classifier, the classification accuracy of the proposed algorithm will be gradually improved as the training time increases, and gradually be stable within a certain range of accuracy, this method can improve the accuracy of imbalanced data classification.
External Filtering and Wavelet Domain Thresholding-based Denoising Method for AWGN corrupted images

He is the author of 31 books, including several on computer security, forensics, and cryptography.His books are used at over 60 universities.He has also authored scientific papers (over 70 so far) on digital forensics, machine learning/AI, cyber warfare, cryptography, bio-engineering, and applied mathematics.He is an inventor with 22 computer science patents.He holds a Doctor of Science (D.Sc