Reviewerly/exHarmony huggingface dataset:
A survey on Bayesian inference for Gaussian mixture model

Clustering has become a core technology in machine learning, largely due to its application in the field of unsupervised learning, clustering, classification, and density estimation. A frequentist approach exists to hand clustering based on mixture model which is known as the EM algorithm where the parameters of the mixture model are usually estimated into a maximum likelihood estimation framework. Bayesian approach for finite and infinite Gaussian mixture model generates point estimates for all variables as well as associated uncertainty in the form of the whole estimates' posterior distribution. The sole aim of this survey is to give a self-contained introduction to concepts and mathematical tools in Bayesian inference for finite and infinite Gaussian mixture model in order to seamlessly introduce their applications in subsequent sections. However, we clearly realize our inability to cover all the useful and interesting results concerning this field and given the paucity of scope to present this discussion, e.g., the separated analysis of the generation of Dirichlet samples by stick-breaking and Polya's Urn approaches. We refer the reader to literature in the field of the Dirichlet process mixture model for a much detailed introduction to the related fields. Some excellent examples include (Frigyik et al., 2010; Murphy, 2012; Gelman et al., 2014; Hoff, 2009). This survey is primarily a summary of purpose, significance of important background and techniques for Gaussian mixture model, e.g., Dirichlet prior, Chinese restaurant process, and most importantly the origin and complexity of the methods which shed light on their modern applications. The mathematical prerequisite is a first course in probability. Other than this modest background, the development is self-contained, with rigorous proofs provided throughout.
Gerakan 5000 Donasi Buku Dalam Upaya Membangun Budaya Literasi : Tahap 4

The society of a nation has a vertical relationship to the quality of the nation. The high interest in reading someone's book influences one's insight, mentality, and behavior. The Indonesian nation is a nation with a low literacy level even though it has been 70 years since Indonesia became an independent country. There are many factors why Indonesian society's literacy has a low percentage. These problems must immediately get serious attention not only from the government but from all of us. How does the discourse about " interest in reading " be carried out for all people when we still have a limited number of books read? So the book donation movement is in an effort to build a culture of literacy and literacy in Indonesia and in Banten in particular. When the state of literacy becomes a culture in Indonesia, it is not impossible that our nation will be an advanced nation.
A New Bidirectional Unsupervised Domain Adaptation Segmentation Framework

Domain shift happens in cross-domain scenarios commonly because of the wide gaps between different domains: when applying a deep learning model well-trained in one domain to another target domain, the model usually performs poorly. To tackle this problem, unsupervised domain adaptation (UDA) techniques are proposed to bridge the gap between different domains, for the purpose of improving model performance without annotation in the target domain. Particularly, UDA has a great value for multimodal medical image analysis, where annotation difficulty is a practical concern. However, most existing UDA methods can only achieve satisfactory improvements in one adaptation direction (e.g., MRI to CT), but often perform poorly in the other (CT to MRI), limiting their practical usage. In this paper, we propose a bidirectional UDA (BiUDA) framework based on disentangled representation learning for equally competent two-way UDA performances. This framework employs a unified domain-aware pattern encoder which not only can adaptively encode images in different domains through a domain controller, but also improve model efficiency by eliminating redundant parameters. Furthermore, to avoid distortion of contents and patterns of input images during the adaptation process, a content-pattern consistency loss is introduced. Additionally, for better UDA segmentation performance, a label consistency strategy is proposed to provide extra supervision by recomposing target-domain-styled images and corresponding source-domain annotations. Comparison experiments and ablation studies conducted on two public datasets demonstrate the superiority of our BiUDA framework to current state-of-the-art UDA methods and the effectiveness of its novel designs. By successfully addressing two-way adaptations, our BiUDA framework offers a flexible solution of UDA techniques to the real-world scenario.
Does the Introduction of Stock Exchange Markets Boost Economic Growth in African Countries

We assess whether the introduction of private equity capital markets effects economic growth in African countries. We address this issue by focussing on stock exchange markets as the predominant type of new equity markets, using a Diff-in-Diff regression method. The analysis uses a panel data set from 48 Sub-Saharan countries over the time range of 1970-2018. 23 countries are part of the “treated” group – which introduced international stock exchanges – and 25 “untreated” countries serve as the control group. Our results show that when compared with the time period prior to the introduction of stock exchange markets, GDP per capita rises by the amount of 532 US$ (around 40% of the Sub-Saharan average) after the introduction of equity capital markets in the treated countries. Over the ten years post introduction, the effect is hump-shaped, with effects becoming statistically significant from the first year after implementation, with a peak in Year 5, and it then becomes statistically insignificant from then onwards.
THE POTENTIAL OF DISCOURSE ANALYSIS IN THE RESEARCH OF PEDAGOGICAL PHENOMENA

The publication is devoted to the study of the potential of the discourse analysis method for conducting pedagogical research. The authors substantiate the relevance and importance of using discourse analysis when working with modern pedagogical sources of information within the framework of the discursive approach. Particular attention is paid to working with theoretical sources of information. Arguments are given in favor of the universality and interdisciplinarity of the described method, and its advantages over traditional methods are described. The technique of discourse analysis from a three-level system is described. The authors emphasize the importance of discourse analysis in the interdisciplinary research and outline the prospects for further research in the field of pedagogical science methodology. Recommendations of the research work design for a novice teacher-researcher are offered.
Abstractive Text Summarization By Using Deep Learning Models

Knowledge is perpetual, a person’s life time isn’t enough to absorb the whole knowledge of the universe. We allare homo sapiens who believe in living beyond the nihilism. We try to seek more and more potentiality in our lives byseeking knowledge. This knowledge these days is stored in various formats in huge repositories mostly in the form ofdocuments, sheets, photos, videos. One finds it difficult to comprehend this whole lot of information. There by, here comesthe need of text summarization. Summarization of documents, text, data is the vital part and a preliminary step in any fieldwhether it is business, social, art, or software. By using machine learning algorithms, the notion of text summarization can beachieved with ease. In this paper we summarize the data as per our requirement i.e., it can be based on output. To achieve thisobjective we are going to use abstractive summarization on single documents. In this process, we perform abstractive textsummarization by using Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU) and Transformers.
CULTURAL DIALOG AS A MULTI-COMPONENT MEANS OF FORMING A TOLERANT PERSONALITY

This paper considers the possibilities of cultural dialog in the formation and education of a tolerant personality. Modern educational paradigms are studies in terms of humanization and humanitarization of education; creative use of tolerance; issues of formation of moral values based on meaningful value bases of human life and society; value attitude to a person; search for the meaning of life through the characters on the example of the works of Razil Valeev. The analysis of scientific literature allows identifying a number of its features: the upbringing of a person as a subject of action; finding a dominant inside the life itself; the formation of a tolerant personality in the context of a cultural dialog, and others. The authors analyze the prose of the famous Tatar writer Razil Valeev. The research complements the theoretical space of the actual pedagogical problem, makes it possible to consider the research in a practical aspect. This is because the proposed model can be used by teachers, school teachers at lessons of national pedagogy, native literature and extracurricular activities for educational work
Implementasi Teknologi Automatic Thermal Air Condition (ATAC) Berbasis Internet of Things (IoT) pada UKM Peternakan Ayam Broiler

Some problems caused covid-19 pandemic, one of serious impact for some bussiness sector as UKM farmer broiler chicken. The government policy to reduce covid-19 infection causes production process and broiler chicken marketing are hampered which is impact to reduce production omset farmer. Through community partnership program (PKM) has been expanded expenditious technology as Automatic Thermal Air Condition (ATAC) based on Internet of Things (IoT) and franchise system which are expected to be able to be problem solving faced by stocker farmer bioler chicken.  The application result of ATAC based on IoT and system franchise significantly can raise farmer productivity through increasing chicken weight, reduce death rate and Feed Conversion Ratio (FCR), supported by right system franchise marketing proven to be able to increase farmer omset.
Integration of the saliency-based seeds generation and random walks with restart for image segmentation

In the task of interactive image segmentation, the user initially indicates some pixels as target seeds and background seeds and propagates the seeds’ labels to the rest of the image. We propose an equidistant seed generation method for interactive image segmentation that combines saliency detection and random walk (RW) with restart with optimal restarting probability. Our method includes two stages: first, we utilize the saliency detection method to obtain the initial target region and generate the initial seeds. Then we relabel the seeds using a Gaussian mixture model with limited user interaction to obtain accurate seeds. The relabeled seeds can limit the range of object; therefore, in the second stage, we can select an optimal restarting probability by calculating the area of the RW that exceeds the limited range of the object seeds. Our method can generate effective seeds and thus reduce the dependence on user interaction. Furthermore, using the optimal restarting probability, we can obtain higher segmentation accuracy. Extensive experiments on the Berkeley segmentation dataset, GrabCut dataset, and MSRA1000 dataset demonstrate that our method can reduce the dependence on user interaction and achieve better performance than the latest interactive image segmentation methods, such as RW, RW with restart, normalized RW, sub-Markov RW, and label propagation through complex networks.
Boosting Image classification using Refined Feature Extraction-A Case study of Image Classification

In real life large amount of data are collect and understand not possible. Here feature extraction helps to reduce the amount of data without losing any important or relevant information. This paper survey on pre-processing, feature extraction for deep convolution neural network, support vector machine classifier. Feature extraction is the process of transforming image data pixel into binary or real value. Feature extraction involves identifying and extracting features based on applications. A designated convolutional neural network feature extraction algorithm extracts most significant features by the first layer of a convolutional neural network or layers of network. Finally, the challenges in convolutional neural network for future extraction research re discussed.Keywords: Feature extract, patch match, convolutional neural network, support vector machine classifier.
3D Reconstruction from public webcams

We investigate the possibility of 3D scene reconstruction from two or more overlapping webcam streams. A large, and growing, number of webcams observe places of interest and are publicly accessible. The question naturally arises: can we make use of this free data source for 3D computer vision? It turns out that the task to reconstruct scene structure from webcam streams is very different from standard structure-from-motion (SfM), and conventional SfM pipelines fail. In the webcam setting there are very few views of the same scene, in most cases only the minimum of two. These viewpoints often have large baselines and/or scale differences, their overlap is rather limited, and besides unknown internal and external calibration also their temporal synchronisation is unknown. On the other hand, they record rather large fields of view continuously over long time spans, so that they regularly observe dynamic objects moving through the scene. We show how to leverage recent advances in several areas of computer vision to adapt SfM reconstruction to this particular scenario and reconstruct the unknown camera poses, the 3D scene structure, and the 3D trajectories of dynamic objects.
The Inappropriateness of English for Specific Purposes (ESP) with Learner’s Goals: A Need Analysis on Communication and Islamic Broadcasting Program

The course of English for Specific Purposes (ESP) is supposed to prepare students for the professional sector, yet the course at IAIN Palopo in Indonesi is designed in general English without any professional input or assessment of the learner's needs. This research is motivated by the Communication and Islamic Broadcasting program students’ complaints of unsatisfaction with the course since it does not meet their needs. This research aims to examine the English needs of students studying in the communication and Islamic broadcasting program. The researchers used a mixed-methods strategy that incorporates both quantitative and qualitative research. The participants in this study were 60 undergraduates and 30 graduate students. Data was gathered through questionnaires and interviews. The data was then analyzed using the comprehensive concept of need analysis proposed by Dudley-Evans &amp; St. John (1998). The results revealed that the majority of students learn English to help them advance in their careers. Their top priority in ESP is to improve their speaking skills, followed by listening, reading, and writing. Due to the repetitive learning method, inappropriate textbook, and short duration, according to the interview results, the students were also unsatisfied with the present ESP course.
평생학습사회 구축에 있어서 교사의 역할

The Lifelong Education Act of South Korea excludes school education, and studies related to school lifelong education focus only on the physical combination between school and lifelong education. I believe this is problematic and this paper deals with the logical relationship between school education and lifelong education. The key argument of this paper is that schools should play an active role in the construction of lifelong learning societies. In particular, teachers should help students discover aptitude and become active learners. I hope that this study can reveal the logical relationship between school education and lifelong education.
Information Technology Risk Analysis In The Personnel Management Information System (SIMPEG) At The Salatiga City Education Office

The Personnel Management Information System is an information system owned by the Education Office that is useful for managing ASN personnel data in Salatiga City. SIMPEG is used as a reference for decision-making for agencies, for example in promotions, as well as joint salary increases. However, in the world of risk management, no matter how good the system is, there is always the possibility of risks that can threaten and disrupt the business processes that run in the use of the information system. Therefore, a risk analysis of IS/IT resources is needed that supports the management of the personnel management information system in the Education Office. By applying the ISO 31000:2018 framework, it is hoped that this risk analysis can minimize the possible risks that exist. The results of this risk analysis are in the form of recommendations for risk actions that are needed according to the priority level of risk from the risk data that has been analyzed. So it is hoped that in the future the Education Office can apply the recommendations for risk actions that have been analyzed in this study.
Elon Musk digs Dogecoin after short-lived Twitter break, cryptocurrency soars

Less than two days after tweeting that he would be taking a break from the social media platform, billionaire Elon Musk was on Twitter again Thursday.
The "Kinesthetic HMD": Enhancing Self-Motion Sensations in VR with Head-Based Force Feedback

The sensation of self-motion is essential in many virtual reality applications, from entertainment to training, such as flying and driving simulators. If the common approach used in amusement parks is to actuate the seats with cumbersome systems, multisensory integration can also be leveraged to get rich effects from lightweight solutions. In this short paper, we introduce a novel approach called the "Kinesthetic HMD": actuating a head-mounted display with force feedback in order to provide sensations of self-motion. We discuss its design considerations and demonstrate an augmented flight simulator use case with a proof-of-concept prototype. We conducted a user study assessing our approach's ability to enhance self-motion sensations. Taken together, our results show that our Kinesthetic HMD provides significantly stronger and more egocentric sensations than a visual-only self-motion experience. Thus, by providing congruent vestibular and proprioceptive cues related to balance and self-motion, the Kinesthetic HMD represents a promising approach for a variety of virtual reality applications in which motion sensations are prominent.
Detection of Criticism and Hate speech Text Formulation on Online Social Network Twitter for Semantic Recommendation System Framework

User opinions on high-volume social media and various themes provide relevant information for sentiment analysis.This information can be collected and analyzed using a natural language processing with a monitoring system to support classification of criticism and hate speech.Regarding monitoring results, a knowledge-based recommendation system with sentiment analysis is supported to send messages to user in order to use positive sentences are not offensive, polite, wise and motivational for users with hateful attitudes.It is important to formulate sentences that can differentiate between criticism and hate speech.By compiling a formula sentence as a classification reference for the text obtained in a twitter tweet whether as criticism or including hate speech.Detection of sentences containing criticism and hate speech using Bag of Word and Convolutional Neural Network to detect hate speech dan criticism sentence via Twitter.The detection results are used for the semantic recommendation system framework that includes sentiment analysis and classification of hate speech.
An Exploratory Study On Origin Of AI: Journey Through The Ancient Indian Texts & Other Technological Descriptions, Its Past, Present & Future

For the modern world and our present civilization the invention of the first programmable digital computer taken place in the 1940s, a machine based on mathematical reasoning, this  knowledge & ideas inspired few scientists to seriously think of building Artificial Intelligence. The modern world also knows that a British Polymath, Alan Turing in the year 1950, suggested the concept of decision science, artificial intelligence and machines solving the real world problems. The first commercial, digital & programmable robot was made by Geroge Devol in 1954, the field of AI research was founded at a workshop held on the campus of Dartmouth College during the summer of 1956. But modern world is not aware of the origin of Artificial Intelligence (AI) began back in 8000 to 11000 years, with myths, stories and rumors of artificial beings endowed with intelligence or consciousness by ancient Rishis of India. The seeds of modern AI were planted by classical philosophers who attempted to describe the process of human thinking as the mechanical manipulation of symbols. This work culminated through Knowledge and ideas on many of the technological advancement that we are witnessing today had already been articulated in holy books of Hinduism like The Ramayana, The Mahabharata, The Bhagawatgeeta, The Vedas & Upanishads which were believed to be written 5000 to 8000 years ago (3000 BC – 6000 BC). Those are not only the holy epics of Hindu civilization but the proof of the existence of India. The contents of the Ancient Indian Texts written in Oldest language of human existence ‘The Sanskrit’ also viewed as ‘Natural Language’ from modern scientific point of view. Elements of modern science present in the Upanishads and Advaita Siddhanta and the nature of maya resembles modern scientific awareness. This awareness is further used in understanding human mental processes and the ways to model them contributing to the natural language comprehension field of artificial intelligence. Vedic concepts are suitable as well as necessary for an efficient lead and the future of Artificial Intelligence (AI). The concept is to bound the man-made machines with the ideology described in the Vedic scriptures, to build a better and smarter world with better machines. Natural language processing with natural language inputs and outputs provides a better human-machine interface. This paper explores origin of the concept of Artificial Intelligence and its existence in ancient Indian Texts and other technological description with modern scientific proofs of them; also reviews Sanskrit language as a possible natural language input to computers.
What Kids Are Reading 2021 – The Summary

Did you know that 2021 marks the 13th year of our What Kids Are Reading report? The report is the largest annual study of the reading habits and ...
No-signaling-proof randomness extraction from public weak sources

The extraction of randomness from weakly random seeds is a topic of central importance in cryptography. Weak sources of randomness can be considered to be either private or public, where public sources such as the NIST randomness beacon broadcast the random bits once they are generated. The problem of device-independent randomness extraction from weak public sources against no-signalling adversaries has remained open. In this paper, we show protocols for device-independent and one-sided device-independent amplification of randomness from weak public Santha Vazirani (SV) sources that use a finite number of devices and are secure against no-signaling adversaries. Specifically, under the assumption that the device behavior is as prescribed by quantum mechanics the protocols allow for amplification of public $ε$-SV sources for arbitrary initial $ε\in [0,0.5)$. On the other hand, when only the assumption of no-signaling between the components of the device is made, the protocols allow for amplification of a limited set of weak public SV sources.