Reviewerly/exHarmony huggingface dataset:
A Descriptive Study to Assess the Knowledge and Attitude Regarding Breast Self-examination among Girls in Selected Colleges of the City and to Develop and Disseminate an Informational Booklet on Breast Self-examination

Background: Prevention is better than cure measures should be taken to prevent cancerous lesion by detecting it at earliest stage. Breast screening in general population has shown to reduce mortality and helps to detect it at earliest stage. Breast self-examination is a technique that all women can use to assess their own breasts. Women familiar with their own normal breast characteristics can easily notice the development of abnormalities early. Each woman and girls should be aware of her own risk factors with regular breast self-examination malignancy may be discovered early and effectively treated. Regular monthly breast self-examination is an essential health maintenance activity. Objective: (1) To assess the knowledge regarding breast self-examination among girls. (2) To assess the attitude regarding breast self-examination among girls. (3) To associate the level of knowledge regarding breast self-examination among girls with selected demographic variables. (4) To associate the attitude regarding breast self-examination among girls with selected demographic variables. Material and Method: The study was conducted in selected colleges of the city. Descriptive approach was used in this study. 100 girls in selected colleges of the city were selected for the study. Semi-structured knowledge questionnaire and rating scale were used to collect the data. Result: Majority of samples, i.e., 54% of them were having average level of knowledge score, 35% of them had good level of knowledge, 9% had poor level of knowledge score, and only 2% had very good and none of the sample, i.e., 0% were in excellent knowledge score and majority of the samples, i.e., 99% of the samples had positive attitude towards breast self-examination, and only 1% had neutral attitude towards breast self-examination and no one had negative attitude score regarding breast self-examination. Conclusion: After detailed analysis, it was found that there is significant association of level of knowledge score in relation to their previous knowledge about breast self-examination and source of information. It is observed by the study that there is significant association of level of attitude score in relation to their mothers educational status and source of information.
Supporting the modernisation of research practices: Efficiency, Scalability, Openness

Unconference held 7 & 8 November 2019Arts West building, University of Melbourne, as part of theAIMOS 2019 Interdisciplinary Meta-research & Open Science conference. Synopsis: There are many opportunities for individual researchers and teams to adopt more efficient, reproducible, accessible, and impactful research processes, tools and workflows. Facilitating and encouraging engagement with such professional development remains a challenge where institutions may be unwilling to invest, and academics are under time pressure, and reluctant to change well-practiced and proven effective strategies. Monash’s Data Fluency, UniMelb’s Research Platform Services, and ANZORN will share how they address these challenges, and facilitate a discussion about what can be learned from their models, what they can learn from you, & how we can collectively uplift research practices.
A database of two-dimensional images of footwear outsole impressions

Footwear outsole images were obtained from 150 pairs of used shoes. The motivation for constructing the database was to enable a statistical analysis of two-dimensional (2D) images of shoe outsoles, to understand within shoe (between replicate images of the same shoe) and between shoe variability, and to develop methods for the evaluation of forensic pattern evidence of shoeprints. Since we scanned the outsole of the used shoes, the images capture not only the outsole pattern design but also the marks that arise from wear and tear and that may help identify the shoe that made the impression. Each shoe in a pair was scanned five times, so that replicate images can be used to estimate within-shoe variability. In total, there are 1500 2D images in the database. The EverOS footwear scanner was used to capture the outsole of each shoe. The scanner detects the weight distribution of the person wearing the shoe when he or she steps on the scanning surface. It images the portions of the outsole that make contact with the scanning surface. The database is a useful resource for forensic scientists or for anybody else with an interest in image comparison. The database we describe, was constructed by researchers in the Center for Statistics and Applications in Forensic Evidence (CSAFE) at Iowa State University.
WIPO Conversation on Intellectual Property (IP) and Artificial Intelligence (AI)

Submission to the World Intellectual Property Organization's Conversation on Intellectual Property (IP) and Artificial Intelligence (AI), second session, on behalf of the Global Expert Network on Copyright User Rights.
QWERTY Keyboard in Virtual Domain Using Image Processing

Individuals inside the cutting-edge times are occupied with genuine issues at hand and they don't have even one moment to squander. They battle to reduce their regular work by utilizing standard gadgets like Desktop Computers and Laptops, moreover further developed gadgets like cell phones and PCs. To improve the versatility and utility people will in general cut back the size of the gadgets. In this way the greater part of the cell phones and hand-held gadgets contain tiny keypads. Some of the people who utilize such a device think that it’s hard to see the letters on the console. With a cell phone, a full-size physical keypad isn't perfect. Yet, options are accessible as written recognition, speech recognition and so forth but every one of them has severe short comings on the exactness and accommodation of a full-size keypad. This paper displays an imaginative virtual keyboard to beat the previously mentioned issues, which may be a feasible swap for fold-up keypad. The proposed device basically dependent on the vision based human-PC cooperation concept, image capturing and image processing technique that contains virtual keys similar to the size of conventional keys inside the ordinary QWERTY keyboard. This device comprises of 2 fundamental modules, in particular, Image Capturing, Character Identification and Mapping. The final product of the virtual keyboard project was a cost-effective, easy to understand and transportable virtual keyboard, that sends typed characters to any display device.
Facial Expression Recognition Using CNN

Facial expressions is non-verbal way of communication among humans through face-face interaction. In recent decades Automatic Expression Detection in an Image or a Video plays an important role due to their drastic application such as Detection of emotions in Psychological Analysis, Cyber Forensics, Emotions Detection in Streaming or stored video for behavioral Analysis. Machine learning Algorithm other than the Neural Network requires complex Feature Extraction Phase followed by the Classification of Emotions, whereas in Classification the accuracy of the model is also less. Traditional Feature Extraction during training phase is also more time consuming. To overcome the difficulties of traditional Approach, Deep Learning Approach called Convolution Neural Network is used to Detection Facial Expression. In Convolution Neural Network, the feature extraction is done by training the Network with the large Facial Expression Image Dataset. The Accuracy of Classification also outperforms than the traditional Machine Learning Algorithms and reaches the States of Art method. Kaggle Facial recognitionFERC-2013 dataset is used.
A Comparative Analysis of the descriptions of the Treaty on basic relations between the Republic of Korean and Japan in Elementary and Middle School Social Textbooks

식민지배의 기억과 청산에 관한 한국과 일본의 입장 차는 양국의 긴장 관계를 초래하는 주된 원인이 되고 있다. 일본은 한일기본조약에 따라 보상이 이루어졌다고 주장하고, 한국은 식민지배에 대한 개인 청구권이 유효하다고 주장한다. 한일기본조약에 대한 양국의 견해차는 국가 간 갈등을 가져오고 있다. 이 연구는 사회 교과서에 각 국가의 담론이 들어있다고 가정하고, 한일기본조약에 관한 한일 양국의 초&#8231;중학교 교과서 서술을 분석·비교하였다. 분석 결과는 다음과 같다. 첫째, 초등학교 사회과 교과서에서는 한일기본조약의 내용이나 조약이 맺어질 당시 세계사와 관련한 내용은 생략되거나 자세하게 다루지 않았다. 둘째, 교과서는 한일기본조약의 내용과 평가, 일본군‘위안부’와 강제징용 문제, 앞으로의 갈등 해결에 대해 양국의 관점에서 기술되었다. 셋째, 과거사 청산과 관련된 한일 갈등에 대한 해결을 위해 한국 교과서는 민족을 넘어선 인권 문제로 확장하여 다루지만, 일본은 국제법상의 약속인 조약으로 법적 해결이 되었다고 기술한다. 넷째, 한일기본조약과 관련하여 샌프란시스코강화조약을 바라보는 관점에 차이를 보였다. 하나의 사건은 그 나라의 사회적 맥락 따라 공적 담론으로 만들어진다. 하나의 공적 담론은 다른 담론과 만나 논쟁의 장을 만들어 간다. 한일 연구자들이 공동으로 사회과 교과서 담론을 분석하고 해석하는 과정에서 쟁점에 따라 서로 다른 생각을 보여주었다. 이를 통해 연구자들은 논쟁 상황을 비판적 사고로 바라보고 문제 해결을 위한 대화와 타협을 강조하는 사회과 교육이 가진 의미를 나누며 소통하는 중요한 시간을 가질 수 있었다.South Korea and Japan s stance on memories of Japanese colonial history and Japan was a big impact on the relationship between Korea and Japan. Japan claims that compensation was made through “the Treaty on Basic Relations between the Republic of Korea and Japan”. but, South Korea claims that it has individual rights to ask Japan for compensation. Therefore, the difference between the two countries has become a conflict. The study defined social textbooks as containing discourse from each country and compared and analyzed how they describe the same historical event. The following is the analysis result. First, elementary school social studies textbooks do not record the details of Treaty on Basic Relations between the Republic of Korea and Japan, and the world history at that time. Second, textbooks describe their content from the standpoint of each country. Third, Korea approaches the resolution of conflict between Korea and Japan as a human rights issue. However, it is stated that Japan was resolved under international law. Fourth, Korea and Japan differ in their view of the San Francisco Enforcement Treaty. An event is created through public discourse according to the political, historical and social context of the country. One public discourse is in conflict with another. Likewise, in the process of jointly analyzing and interpreting social studies textbook discourse, researchers from Korea and Japan showed different thoughts according to issues. Through this, we were able to explore the meaning of social studies education as a global citizen education.
Labelled Natural Deduction for Public Announcement Logic with Common Knowledge

Public announcement logic is a logic that studies epistemic updates. In this paper, we propose a sound and complete labelled natural deduction system for public announcement logic with the common knowledge operator (PAC). The completeness of the proposed system is proved indirectly through a Hilbert calculus for PAC known to be complete and sound. We conclude with several discussions regarding the system including some problems of the system in attaining normalisation and subformula property.
Spherical approach: Objects Tracking in Catadioptric System Using The GGD Distribution

The objects tracking applications are ubiquitous and largely discussed in computer vision field. Nevertheless, the toughest challenge encountered in the catadioptric system is images geometry deformations. Nevertheless, these images have significant distortions that that bring us to take them into account during processing. In this paper, we propose an adapted tracking according to spherical coordinates over the 2D image. We present a novel content based omnidirectional image provided by the catadioptric system for object tracking model using a Spherical object tracking (SOT). Our statistical approach uses a new search algorithm called Ring Search (RSA), the Generalized Gaussian Distribution (GGD) as well as the Kullback-Leibler Distance (KLD). In SOT, we split images into several macro-blocks according to spherical coordinates, each macro-block are modelled by the GGD parameters. After that, we compute the similarity between the current bloc and the candidate one onto the search zone in the next frame. Experimental results in spherical space show that the SOT outperforms efficiently the adaptive Mean-Shift in visual tracking in term of Spatial Overlapping Estimation (SOE) and the ROC curve.
Natural Language Understanding for Simultaneous Conference Interpretation

Conference interpretation is an active area of linguistics with growing challenges in technological integration. Despite advancement in information technology, simultaneous interpreters have not yet been provided with adequate tools to bring down the stress level that accompanies their profession. The booth setting and the way they perform have not been changed a lot over the years. Although a number of computer approaches have been presented to make the task of conference interpreters less challenging, most of them fail to meet their actual needs. Some of those approaches add to the pressure that interpreters are already under as they require human input, while others are restricted to certain languages. This paper proposes a new approach that makes use of automatic speech recognition (ASR) combined with a cloud-based machine translation (MT) that transcribes spoken words and provides in-depth translation in a contextual manner through the use of a compiled glossary. The proposed approach provides for the first time an instantaneous transcription of a speech, a domain detection through a part-of-speech tagger, and an adequate translation of the terminology used. Our approach has been tested in terms of transcription accuracy, domain extraction, and terminology identification and retrieval using English and Arabic speeches that cover different domains.
The Impact of Artificial Intelligence: brave new world

The UKeiG Members’ Day, held at CILIP HQ on Friday 7th June 2019, showcased three experts: Michael Upshall (UNSILO), David Haynes (City, University of London) and Dr. Tony Russell-Rose (UXLabs, 2dSearch.) The event explored the impact of artificial intelligence on the knowledge, information management and library profession. Upshall kicked off the event by throwing down a gauntlet. Were taxonomies still relevant in an age when AI was transforming search by enabling concept clustering and semantic enrichment? Manual classification schemes, vocabularies, taxonomies and ontologies have always played an essential role in information retrieval but Upshall argues that they are expensive and fundamentally flawed; reactive not proactive. “They will never be complete. They will never be large enough.” Haynes went on to explore the potential impact of AI on the information resource management cycle, leaving Russell Rose to deliver an illuminating crash course on the linguistic phenomena that make natural language processing (NLP) such a complex and multi-faceted field of research. “Language is ambiguous,” he said, “and the key tenet of NLP is resolving that ambiguity.” There was a consensus amongst the delegates that there are huge challenges and opportunities ahead for the LIS profession; that information science is fundamental to AI.Keywords: AI, Artificial Intelligence, Alogorithms, Information Retrieval, Search, Machine Learning, Taxonomies, Natural Language Processing, NLP, Information Science.
Stacked Filter Bank based descriptor for Human Action Recognition from Depth Sequences

Registering the motion cues from a video to produce a compact representation is a crucial stage in video based Human Action Recognition (HAR). Exploiting the most prominent features using an efficient descriptor from such a representation also plays equally significant role in the performance of recognition models. In this work, we present a concise Depth Motion Map with striding which registers the motion cues from depth sequences on a video and a novel Filter Bank based descriptor, wherein a Taylor Series Expansion (TSE) filter, a Riesz filter and a gradient filter are stacked together to extract the prominent features. We empirically evaluate the feasibility of our method on MSR Action 3D dataset under standard protocols, achieving state-of-the-art results.
Sample-Conditioned MSE of Error Estimation

There are two sources of randomness in the Bayesian model. The first is the sample, which randomizes the designed classifier and its true error. Most results on error estimator performance are averaged over random samples, which demonstrates performance relative to a fixed feature-label distribution. The second source of randomness is uncertainty in the underlying featurelabel distribution. The Bayesian MMSE error estimator addresses the second source of randomness. This gives rise to a practical expected measure of performance given a fixed sample and classifier.
STUDYING THE PROPERTIES OF NITROGEN USING INFORMATION AND COMMUNICATION TECHNOLOGY

In the world, special attention is paid to the modernization of chemical education, the introduction of innovative technologies, and the improvement of the methodological basis of teaching in line with modern trends. Effective research is being conducted to improve the quality of teaching chemistry internationally, to integrate innovative and information technologies into the educational process, to use the opportunities of mixed education (blended learning), to create modern methodological support for the development of students' mental abilities and creative abilities. Wide-ranging reforms are being implemented in the educational system of the country to introduce advanced learning technologies and information and communication technologies into the learning process, increase the intensity and effectiveness of training, and adapt to the world standards. At the same time, there is a need to develop advanced mechanisms of teaching methods based on innovative technologies in the teaching of chemistry as a holistic system it was found that they did not know how to effectively use virtual labs and animation in their labs and workshops, to identify the gaps in their students' knowledge and to improve them using a quantitative approach to address them. For this purpose we have set ourselves goals and objectives and are achieving good results.
Exploring Relevance as Truth Criterion on the Web and Classifying Claims in Belief Levels

The Web has become the most important information source for most of us. Unfortunately, there is no guarantee for the correctness of information on the Web. Moreover, different websites often provide conflicting information on a subject. Several truth discovery methods have been proposed for various scenarios, and they have been successfully applied in diverse application domains. In this paper, we have attempted to answer the question whether the truth is relevant. We conducted an experimental study in which we analyzed and compared the results of two different truth discovery methods: Relevance-based sources ranking and Majority vote. We have found that the truth is not always held by the most relevant sources on the web. Sometimes the truth is given by the majority vote of the crowd. In addition, we have proposed a method of presenting the results of truth discovery with gradual degrees of belief. A method that allows to configure and target the desired level of trust.
IDENTIFICATION OF LUNG CANCER STAGES USING EFFICIENT MACHINE LEARNING FRAMEWORK

Lung cancer is a major global health problem. Despite advances in prevention, diagnostics and therapies in the past decade, lung cancer is the leading cause of cancer-related morbidity and mortality worldwide Patients diagnosed with non-small cell lung cancer (NSCLC; 85% of lung cancers) are most often diagnosed at late stages, associated with dismal prognoses. Convolutional Neural Networks (CNNs) models become main stream among the identification zone in light of their promising result on creating significant level image representations. A new machine learning design for learning significant level image portrayal to accomplish high order precision with low change in clinical picture order assignments is proposed. The purpose of personalized medicine is to identify the optimal treatment for each individual patient, to maximize treatment benefit and minimize adverse effects. Informative biomarkers which can reliably predict outcome are needed to achieve this goal. This manuscript proposes an Efficient Machine Learning Algorithm (EMLA) for identification of different stages of lung cancer. The proposed method is compared with the traditional methods and the results show that the proposed method is better than existing methods.
A Study on the Content Elements and Systematization of Korean Ancient History in Secondary Textbooks

Systematization has become a problem with each revision of the curriculum. The systematization should be based on content, not on form. In this sense of problem, this paper reviewed the research performance of ancient history and presented a method of systematization based on it.BR While the research of ancient history is diversified and subdivided, I think the core content of ancient history is, after all, “an ancient country,” and it is possible to systematize by school grade according to how to teach the ancient country. In middle school curricula, we selected content elements based on development of individual countries with historical facts. And in high school, we selected content systems and content elements based on subjects.BR In particular, the subject-oriented content has the advantage of introducing new materials or actively reflecting the academic research achievements.
ANDROID-BASED SALES INFORMATION SYSTEM CASE STUDY ON NABILA BAKERY BREAD FACTORY GORONTALO CITY

Sales information system is a system designed to simplify the online sales process. Based on research at Roti Nabila Bakery Factory researchers found problems in the Promotion System that only relied on Sales in conducting sales promotions, Ordering system is still recorded in a piece of paper, Calculation of total sales transactions still use calculator tools and Sales Reports are still recorded in a Sales Book so The researcher wants to Design a Sales Information System Application to solve the problems that exist in the research site. This study uses whitebox and blackbox testing. Whitebox testing is testing with trial techniques on program flow, logic structure and program procedures by flowchart mapping, then calculating the number of edges and nodes. Black box testing method focuses on the functional requirements of the software. Therefore black box trials allow software developers to create a set of input conditions that will train all the functional requirements of a program whether it runs as expected or vice versa. Based on the results of examining Whitebox in one of the processes in this system, namely on the Ordering of bread menu with a balanced yield of Cyclometic Complexity (CC) = 4, this system is stated to work well. While the results of the Blackbox system test can run as expected. Keywords: Information System, Sales, Android, php, html and Mysql.
Research and Application of Face Detection Algorithm Based on Depth Map

Face detection is an active research area in the field of computer vision. It can be applied to various applications as the basis of specific fields such as face recognition and human-computer interaction. For a long time, the complex external environment has a huge impact on the accuracy of face detection, especially the different illumination will make the gray level distribution of 2D face images uneven, resulting in sharp increase of local contrast and affecting the accuracy of face detection. In order to solve this problem, this paper has developed a face detection method based on depth map with haar-like features. To verify our work, the traditional face detection algorithm in OpenCV is compared with ours under different illumination conditions.
Investigating the Spark

In May, we look at lightning—what it tells us about dangerous weather, how to find it on other planets, and what we might learn if we get all that data in one place.