Reviewerly/exHarmony huggingface dataset:
Prosody-based speech synthesis by unit selection for Arabic

This work aims to develop a high quality Arabic concatenative speech synthesis system based on unit selection. The original unit selection algorithm was modified to integrate more phonological, linguistic and contextual features in order to improve the selection cost calculation fromone side, and more prosodic parameters for more exact concatenation cost estimation from the other side. The objective and subjective assessments based respectively on SER (Signal-to-Error Ratio) and on MOS (Mean Opinion Score) tests show satisfactory results.
Research Guides: Authority: Critical Evaluation

This guide will help you better understand authority in the context of research and information and provide you with methods of evaluating an information source to determine its authority.
αVIL: Learning to Leverage Auxiliary Tasks for Multitask Learning

Multitask Learning is a Machine Learning paradigm that aims to train a range of (usually related) tasks with the help of a shared model. While the goal is often to improve the joint performance of all training tasks, another approach is to focus on the performance of a specific target task, while treating the remaining ones as auxiliary data from which to possibly leverage positive transfer towards the target during training. In such settings, it becomes important to estimate the positive or negative influence auxiliary tasks will have on the target. While many ways have been proposed to estimate task weights before or during training they typically rely on heuristics or extensive search of the weighting space. We propose a novel method called α-Variable Importance Learning (αVIL) that is able to adjust task weights dynamically during model training, by making direct use of task-specific updates of the underlying model's parameters between training epochs. Experiments indicate that αVIL is able to outperform other Multitask Learning approaches in a variety of settings. To our knowledge, this is the first attempt at making direct use of model updates for task weight estimation.
Grounding Language to Entities for Generalization in Reinforcement Learning

In this paper, we consider the problem of leveraging textual descriptions to improve generalization of control policies to new scenarios. Unlike prior work in this space, we do not assume access to any form of prior knowledge connecting text and state observations, and learn both symbol grounding and control policy simultaneously. This is challenging due to a lack of concrete supervision, and incorrect groundings can result in worse performance than policies that do not use the text at all. We develop a new model, EMMA (Entity Mapper with Multi-modal Attention) which uses a multi-modal entity-conditioned attention module that allows for selective focus over relevant sentences in the manual for each entity in the environment. EMMA is end-to-end differentiable and can learn a latent grounding of entities and dynamics from text to observations using environment rewards as the only source of supervision. To empirically test our model, we design a new framework of 1320 games and collect text manuals with free-form natural language via crowd-sourcing. We demonstrate that EMMA achieves successful zero-shot generalization to unseen games with new dynamics, obtaining significantly higher rewards compared to multiple baselines. The grounding acquired by EMMA is also robust to noisy descriptions and linguistic variation.
Bayes estimates of multimodal density features using DNA and Economic Data

In several scientific fields, like bioinformatics, financial and macro-economics, important theoretical and practical issues exist that involve multimodal data distributions. We propose a Bayesian approach using mixtures distributions to approximate accurately such data distributions. Shape and other features of the mixture approximations are estimated including their uncertainty. For discrete data, we introduce a novel mixture of shifted Poisson distributions with an unknown number of components, which overcomes the equidispersion restriction in the standard Poisson which accomodates a wide range of shapes such as multimodality and long tails. Our simulation-based Bayesian inference treats the density features as random variables and highest credibility regions around features are easily obtained. For discrete data we develop an adapted version of the Reversible Jump Markov Chain Monte Carlo (RJMCMC) method, which allows for an unknown number of components instead of the more restrictive approach of choosing a particular number of mixture components using information criteria. Using simulated data, we show that our approach works successfully for three issues that one encounters during the estimation of mixtures: label switching; mixture complexity and prior information and mode membership versus component membership. The proposed method is applied to three empirical data sets: The count data method yields a novel perspective of the data on DNA tandem repeats in \cite{DNA_leiden}; the bimodal distribution of payment details of clients obtaining a loan from a financial institution in Spain in 1990 gives insight into the repayment ability of individual clients; and the distribution of the modes of real GDP growth data from the PennWorld Tables and their evolution over time explores possible world-wide economic convergence as well as group convergence between the US and European countries. The results of our descriptive analysis may be used as input for forecasting and policy analysis.
A microwave monitoring service for the study of the Stromboli volcano deformation

&amp;lt;p&amp;gt;In this paper, we present the activities relevant to the microwave monitoring of the Stromboli volcano ground deformation, performed by IREA-CNR (Institute for the Electromagnetic Sensing of the Environment) and UNIFI (University of Florence) as Centres of Competence for the Italian Civil Protection Department.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The availability of Synthetic Aperture Radar (SAR) system provides, among several techniques, accurate information on the volcano morphology and deformation, thus allowing us to understand the on-going volcanic changes. In this work, we present the results of a back-analysis (from 2015) of the volcano behaviour in terms of ground deformation and an insight on the volcano crisis occurred from July 3 2019, by using Differential Interferometry SAR (DInSAR) measurements.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The generated DInSAR results are both satellite and ground based. In particular, we show the displacement time series obtained with Sentinel-1 data acquired from March 2015 to October 2019 over the whole island and from ascending and descending orbits, and the displacement estimated with a Ground-Based SAR placed for the Sciara del Fuoco and summit craters sensing.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Moreover, the combination of the deformation measurements retrieved with both monitoring systems, which are characterized by independent acquisition geometries, allowed us to partially reconstruct a 3D deformation field of Sciara del Fuoco area.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Finally, we show the preliminary result of a test about an operational monitoring service based on new methodologies for the processing of airborne SAR data, aimed at evaluating its relevance for Civil Protection purposes in volcanic risk context.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;strong&amp;gt;&amp;amp;#160;&amp;lt;/strong&amp;gt;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;This work is supported by the 2019-2021 IREA-CNR and Italian Civil Protection Department agreement, and by the 2019-2021 UNIFI and Italian Civil Protection Department agreement.&amp;lt;/p&amp;gt;
Good Actors can come in Smaller Sizes: A Case Study on the Value of Actor-Critic Asymmetry.

Actors and critics in actor-critic reinforcement learning algorithms are functionally separate, yet they often use the same network architectures. This case study explores the performance impact of network sizes when considering actor and critic architectures independently. By relaxing the assumption of architectural symmetry, it is often possible for smaller actors to achieve comparable policy performance to their symmetric counterparts. Our experiments show up to 97% reduction in the number of network weights with an average reduction of 64% over multiple algorithms on multiple tasks. Given the practical benefits of reducing actor complexity, we believe configurations of actors and critics are aspects of actor-critic design that deserve to be considered independently.
navalang That would be owning your own ...

@navalang That would be owning your own domain and using #indieweb building blocks, at least as a start.
Ljudmodulering och Visuell Representation av Musik

The ambition of this project was to create, program and control a matrix of individually controllable LEDs. This was achieved by utilizing a variety of microcomputers, such as Arduino, and by forgi ...
Comparing support vector machine and random forest to predict ovarian cancer

The third most common female cases of cancer in Indonesia is Ovary Cancer. Ovary cancer or ovarian cancer, affecting one or both ovaries, is a heterogeneous disease. The factors which increase risk of ovarian cancer are more pregnancies, early menstruation and late menopause, obesity, family history, and BRCA1 or BRCA2 mutation. Ovarian cancer can be diagnosed by physical test, pelvic test, transvaginal ultrasound test, x-ray, MRI scan, CT scan, or CA 125.  Patients of ovarian cancer who are treated should do regular checkup, because it may come back. This research uses data of ovarian cancer examination result from RS Al Islam Bandung hospital. The method that used are Support Vector Machine (SVM) and Random Forest method. SVM is the classification method that uses discriminant hyperplane, dividing to classes. Then, Random Forest is a tree-based ensemble depending on a collection of random variables. SVM and Random Forest are applied to predict ovarian cancer data, then the results of each methods are compared. Random Forest method is better than SVM with the accuracy value is 100%.
Research Guides: Consortium Loan Service (CLS): Ordering from your Home Library

This guide is designed to facilitate users through the borrowing of consortium books, known as the Consortium Loan Service (CLS)
A Near-Optimal Recipe for Debiasing Trained Machine Learning Models

We present an efficient and scalable algorithm for debiasing trained models, including deep neural networks (DNNs), which we prove to be near-optimal by bounding its excess Bayes risk. Unlike previous black-box reduction methods to cost-sensitive classification rules, the proposed algorithm operates on models that have been trained without having to retrain the model. Furthermore, as the algorithm is based on projected stochastic gradient descent (SGD), it is particularly attractive for deep learning applications. We empirically validate the proposed algorithm on standard benchmark datasets across both classical algorithms and modern DNN architectures and demonstrate that it outperforms previous post-processing approaches for unbiased classification.
PERANCANGAN BUKU CERITA BERGAMBAR BERWARNA UNTUK ANAK TK STUDI KASUS DI TK HARAPAN MASA

Current technological developments make many children choose to play with their gadget. This makes them sometimes lazy to read a book. But that can be tricked by story bookspictorial. The picture book itself has several advantages besides drawings that attract children's attention. Like an easy story to understand, contain meaning or stories of life learning, enhance imagination, and the existence of pictures in the story book will give a picture of imagination and fantasy in children. Therefore children are advised to be fond of reading book. Picture books have many variations on the theme the story, like about friendship or other fable stories. And for children who don't like books, can start with this picture book. Can be started by looking at the pictures, then just learning to read contents of the story of the book. In kindergarten HARAPAN MASA itself reading activities the book is still lacking. Most teachers read later students mimic. This is still considered inefficient because not all children will pay attention to. By holding the book reading activity, children are expected TK HOPE MASA can more smoothly read a book In collecting data, the method used by the author is by using interview research methods, surveys, literature studies. For making it using the CorelDRAW X7 program, Adobe Illustrator CS6, Adobe Photoshop CS5 and Manga Studio 5. The existence of this picture book is expected to increase children's interest in reading books.
A usability testing on jawi mobile application for standard one acquisition on reading and writing skills / Siti Shafida Sharifuddin, Nur Hasni Nasrudin and Rosida Ahmad Junid

Usability testing is one of the most profound product-evaluation methods that can be applied to determine the effectiveness of an innovation, especially how the product invented meets the user's need and expectation. However, the problem is that there are some believes that usability testing is pointless because real users would test the application and report any issue arises. Notwithstanding this belief, the researchers still think that usability testing can highlight the quality of user experience and can answer the question of whether people enjoy the application or not. Thus, this paper will expose the readers to the usability testing that is conducted on a new Jawi Mobile Application that adopts Augmented Reality (AR) technology and used ADDIE research method, which aims to improve Standard One student's skills in reading and writing the Jawi script. Thirty students (30) of standard one aged 7 years old from a chosen primary school were involved in the usability test. The usability test involved questionnaires and observations based on four acceptance test elements. Based on the findings, it is proven that the new Jawi Mobile Application that uses Augmented Reality (AR) Multimedia Elements is a breakthrough innovation which firstly, can help to ameliorate standard one basic acquisition on Jawi reading and writing skills, and secondly can be integrated into the Standard One School Syllabus.
A Deep Learning-based Obstacle Classification Method from Partial Visual Information: Application to the Assistance of Visually Impaired People

Hidden text: The abstract may be included at the discretion of the supervisor.Among the challenges that face visually impaired people is how to navigate safely, recognize encountered obstacles, and move independently from one location to another in unknown environments. Obstacle detection and classification are among the most challenging difficulties that hinder a visually impaired person from performing daily tasks. By proposing a solution towards overcoming these challenges, this work will be of most importance to visually impaired people. In this work, we propose a consistent, reliable and robust smartphone-based method to classify obstacles in unknown environments from partial visual information based on Multi-layer Perceptron (MLP) technique. Our proposed method deals with high levels of noise and bad resolution in the captured frames. In addition, it offers a maximum flexibility to the user and use the least expensive equipment possible. Moreover, our method, leveraging on deep-learning techniques, enables to semantically categorize the detected obstacles in order to increase the awareness of the explored environment. The efficiency of the work is measured by many experiments studies on different complex and unknown scenes. It records high accuracy of [90.2%].
Women Existence in The Novel Men Coblong by Oka Rusmini as A Teaching Material

Fictional works describe individual or group problems in an imaginary world. This problem can explore through fictional works such as short stories or novels. The various issues that arise in literary works are products of real life. What needs to be understood is that the literature contains the author's vision and the reader's ideas. More than that, literary works hold some messages and values. On that basis, this study aims to describe and interpret the existence of women in Oka Rusmini's Men Coblong novel. The analysis results of the women characters' presence in the novel expect to use as literary teaching materials in higher education institutions that orientate towards character education. This research is descriptive qualitative research with a feminist approach. This research's data are the existence of female characters in the data source in the form of Oka Rusmini's Men Coblong novel. The data collected using reading and note-taking techniques. The collected data were analyzed using interactive analysis techniques. The results showed that in the MenCoblong novel, there were women who became other figures, intellectual women, and working women. The study results towards women's existence in Men Coblong novel can use as literary teaching materials.
The motivation for success, self-regulation, and educational success

There is a significant increase in society's interest in the realization of human intellectual, personal and creative potential as the main source of achievements, which is the basis for the progressive formation of a high-tech society. The achievements of adolescents and young people in education are the potential of the nation and determine the competitiveness required for the further progress and formation of society. Different motivations are applied during vocational training. Among them, cognitive, professional motives, motives for creative achievement, motives for status development, motives for self-realization and material motives have a significant place. One of the main tasks of modernizing the activities of current education, teachers, and school psychological services is to form a student who actively and independently acquires social knowledge, understands the importance of education and self-knowledge for their future life. As a subject of education, the learner is able to selectively and independently set actual and long-term goals, direct and support his activities, organize and also manage educational activities. Key words: self-analysis, self-regulation, education, motivation, purpose, result, vocational training, new educational standards
Pengaruh Teknik SQ4R dan Berpikir Kritis Terhadap Kemampuan Membaca Pemahaman Siswa

This research aims to know: the influence of SQ4R reading techniques on the ability to read understanding of high school students at Daar EL Falaah Regency Pandeglang. The influence of critical thinking on the ability to read understanding private high school students Daar EL Falaah District Pandeglang.The influence of interactive reading techniques and critical thinking towards the ability to read the understanding of private high school students Daae EL Falaah District Pandeglang. This research uses experimental method with design experiments by Treatment 2x2. Quantitative Data is obtained through comprehension reading ability tests and critical thinking tests. Data analysis using ANOVA 2 lanes and processed using SPSS 20 program. The results showed: there is a significant influence of the technique of reading on the ability to read the understanding of private high school students Daar EL Falaah Regency Pandeglang. It is evidenced by the acquisition of Sig. = 0.027 0.05 and Fh = 4.349.
Addressing the Topological Defects of Disentanglement

A core challenge in Machine Learning is to disentangle natural factors of variation in data (e.g. object shape vs pose). A popular approach to disentanglement consists in learning to map each of these factors to distinct subspaces of a model's latent representation. However, this approach has shown limited empirical success to date. Here, we show that this approach to disentanglement introduces topological defects (i.e. discontinuities in the encoder) for a broad family of transformations acting on images ---encompassing simple affine transformations such as rotations and translations. Moreover, motivated by classical results from group representation theory, we propose an alternative, more flexible approach to disentanglement which relies on distributed equivariant operators, potentially acting on the entire latent space. We theoretically and empirically demonstrate the effectiveness of our approach to disentangle affine transformations. Our work lays a theoretical foundation for the recent success of a new generation of models using distributed operators for disentanglement (see Discussion).
Media Pozel (Poster Puzzel) for Learning Javanese Nglegeno Script in Elementary Schools

This study aims to develop Pozel Media (Poster Puzzel) for Learning Javanese Nglegeno Script in Elementary Schools. This research is a development research at the product development stage. The problems of learning Javanese characters in schools are quite diverse. Seeing the various factors that cause and problems learning Javanese script, it is necessary to take strategic resolution steps. One of the strategic ways in learning Javanese script is by developing learning media to help and make it easier to learn Javanese script. This research produces Pozel Media (Poster Puzzel) for Nglegena Javanese Script Learning in Elementary Schools. Pozel is designed with attention to the elements of good media and the characteristics of elementary school students. Pozel is made with a wooden box design so that it is durable if used repeatedly and makes it easy to store so that Pozel cards are not easily lost.
Image Restoration by Group Sparsity with Union of Hierarchical DirLOTs

In this study, we propose to introduce group sparse regularization with multiple Directional Lapped Orthogonal Transforms (DirLOTs) for image restoration. Sparse signal restoration has shown its effectiveness in a wide variety of fields. While $\ell_{1}$-norm regularization is typically used in sparse restoration, a group sparse regularization can restore signals more effectively if sparse structure in signals is organized into groups. As a previous research, a group sparse regularization with dependency between discrete wavelet transform (DWT) coefficients has been proposed and the significance is demonstrated. Since DirLOTs are redundant and symmetric, more effective sparse restoration can be expected than ordinary DWTs. In this work, we introduce group sparse regularization into image restoration with multiple DirLOTs, where the symmetric property is utilized. Through simulations, the restoration performance of the proposed method is shown and the significance is confirmed.
LibGuides: LSC 595 Merchant Professional Field Experience: Home

This guide contains record of my field experience at Concord Free Public Library in the Spring 2021 semester
Hybrid Improved Pre Copy and Post Copy Approach for Virtual Machine Migration in Cloud

With the increasing of rapid demand for cloud resources, load on the cloud server is increased drastically in the past few decades. Live virtual machine (VM) relocation is an important approach for the dynamic scheduling of resources in the cloud environment. The solution for dealing with the dynamic load that transfers the virtual machine from one server to another is virtual machine migration. The cloud provider uses three virtual machine migration techniques such as stop and copy, pre-copy, and post-copy. The pre-copy approach is the most popular approach among all migration approaches but it is not suitable for the write intensive application is running on the virtual machine. This article suggested a hybrid virtual machine solution that would minimize the overall migration time, and downtime. And also there is an increase in the virtual machine's performance. To test the efficiency of the suggested solution, the CloudSim simulation tool is used. Compared to the existing method, the findings of the experiments indicate that the proposed method produces better results.
LibGuides: Science Library Displays: Marie Maynard Daly

A guide that has information about the displays in the science library as well as original content created for displays.