Reviewerly/exHarmony huggingface dataset:
Short-time speaker verification with different speaking style utterances

In recent years, great progress has been made in the technical aspects of automatic speaker verification (ASV). However, the promotion of ASV technology is still a very challenging issue, because most technologies are still very sensitive to new, unknown and spoofing conditions. Most previous studies focused on extracting target speaker information from natural speech. This paper aims to design a new ASV corpus with multi-speaking styles and investigate the ASV robustness to these different speaking styles. We first release this corpus in the Zenodo website for public research, in which each speaker has several text-dependent and text-independent singing, humming and normal reading speech utterances. Then, we investigate the speaker discrimination of each speaking style in the feature space. Furthermore, the intra and inter-speaker variabilities in each different speaking style and cross-speaking styles are investigated in both text-dependent and text-independent ASV tasks. Conventional Gaussian Mixture Model (GMM), and the state-of-the-art x-vector are used to build ASV systems. Experimental results show that the voiceprint information in humming and singing speech are more distinguishable than that in normal reading speech for conventional ASV systems. Furthermore, we find that combing the three speaking styles can significantly improve the x-vector based ASV system, even when only limited gains are obtained by conventional GMM-based systems.
Diversity and inclusion in information architecture : The 7th Academics and Practitioners Roundtable

Diversity and inclusion in information architecture : The 7th Academics and Practitioners Roundtable
A Rule-Based System for Explainable Donor-Patient Matching in Liver Transplantation

In this paper we present web-liver, a rule-based system for decision support in the medical domain, focusing on its application in a liver transplantation unit for implementing policies for donorpatient matching.The rule-based system is built on top of an interpreter for logic programs with partial functions, called lppf, that extends the paradigm of Answer Set Programming (ASP) adding two main features: (1) the inclusion of partial functions and (2) the computation of causal explanations for the obtained solutions.The final goal of web-liver is assisting the medical experts in the design of new donor-patient matching policies that take into account not only the patient severity but also the transplantation utility.As an example, we illustrate the tool behaviour with a set of rules that implement the utility index called SOFT.
Penentuan Awal Waktu Salat Wajib di Kota Sengkang dengan Menggunakan Metode Klasik dan Kontemporer

Abstra ct The main problem in this research is how to determine the beginning of prayer times using classical methods and contemporary methods in Sengkang City. The subject matter is further divided into 1) How to determine the initial prayer time in Sengkang City using the classical method? 2) How to determine the beginning of prayer times in Sengkang City using contemporary methods? The purpose of this study is to obtain information related to how the people of Sengkang city determine the start of prayer time both classically and contemporary. The purpose of this research is to obtain information related to how the people of Sengkang city determine the start of prayer time both classically and contemporary. Researchers make observations, interviews and documentation in order to collect accurate and relevant data for research. This type of research is a qualitative field research in which the researcher collects data directly by going directly to the field to obtain more efficient data, while the data mining technique uses reference books related to research titles, journals, previous theses and observation methods of interviews and documentation. . The results obtained in this study are the first people in the city of Sengkang in determining the time of obligatory prayers using classical methods such as natural phenomena, shadows of objects, animal sounds and using methods compiled by angregurutta H. Muhammad Yunus Martan. Second, the majority of people in the city of Sengkang use the decree of the Ministry of Religion of Wajo Regency, thus indirectly the community uses the contemporary method used by the Ministry of Religion of the District. Wajo, namely using the formula for determining prayer times and using applications for determining prayer times, one of which is a pro Muslim. Implications The research in this thesis is a matter of determining the initial time of the obligatory prayers which the public must understand well. As for the suggestions and hopes from the author, namely, to everyone who covers the issue of worship, especially from the Ministry of Religion and astronomy students to carry out socialization and counseling related to determining the initial time of compulsory prayer. Kata Kunci: Salat, Klasik, Kontemporer
Application of scientific knowledge and the prevention of COVID-19 in México in post-truth times

As a result of the COVID-19 pandemic, Mexicans faced a large amount of information with different opinions (some erroneous) about preventive measures, which could´ve affected the control of the epidemic Possessing knowledge and information does not mean understanding a phenomenon such as this and acting up accordingly Based on a study that recorded the naive ideas of children and young people about microbes and hygiene practices, an online survey (SurveyMonkey platform) of 21 questions about attitudes and behaviours about the pandemic was conducted It was spread on two social networks for a month A national sample was obtained, made up of 701 people with schooling from basic to university level Under the hypothesis that observance of preventive measures to avoid acquiring coronavirus recommended by the Mexican health authorities depends on the educational level of the population, it was found that schooling did not largely affect its implementation However, a significant difference was evident with university students, who knowing more precisely the characteristics of microbes and having a better understanding of the transmission of infectious diseases, provided them with elements to apply critical thinking to make decisions related to self-care behaviours during the pandemic © 2020 Fundacion para la Investigacion Social Avanzada All rights reserved
Harnessing Digital Technology to Strengthen the Culture of Reading at Public Libraries in South Africa

Statistics and numerous authors have highlighted the reading crisis in South Africa. At the same instance, more people in South Africa are embracing the potential of digital technology to provide lifelong learning opportunities and also to strengthen the culture of reading. This study is framed against the backdrop and implementation of the Mzansi Libraries On-Line Project in South Africa – a project implemented in line with the Global Libraries Programme of the Bill &amp; Melinda Gates Foundation. The study explored the potential of access to information of digital technology and the contribution of the project to inculcating a culture of reading at public libraries. A benchmark survey was conducted by an independent research company during the pilot phase of the project in 2015. This survey covered library users of the 27 libraries that formed part of the pilot phase, and a further 25 libraries from a representative sample across South Africa. An end-line survey was conducted through a private company towards the conclusion of the countrywide implementation in 2017, based on the Common Impact Measurement System which was customised for South Africa. The benchmark survey found that although ICT in libraries had been used by relatively few people in 2015, the impact of this technology tended to be positive and would be beneficial to the wider society by helping to redress societal imbalances, including education and the culture of reading. The end-line survey found increased benefits of library usage and library technical infrastructure to improve the lives of the communities involved.
Cooperative Heterogeneous Deep Reinforcement Learning

Numerous deep reinforcement learning agents have been proposed, and each of them has its strengths and flaws. In this work, we present a Cooperative Heterogeneous Deep Reinforcement Learning (CHDRL) framework that can learn a policy by integrating the advantages of heterogeneous agents. Specifically, we propose a cooperative learning framework that classifies heterogeneous agents into two classes: global agents and local agents. Global agents are off-policy agents that can utilize experiences from the other agents. Local agents are either on-policy agents or population-based evolutionary algorithms (EAs) agents that can explore the local area effectively. We employ global agents, which are sample-efficient, to guide the learning of local agents so that local agents can benefit from sample-efficient agents and simultaneously maintain their advantages, e.g., stability. Global agents also benefit from effective local searches. Experimental studies on a range of continuous control tasks from the Mujoco benchmark show that CHDRL achieves better performance compared with state-of-the-art baselines.
Trapped ion quantum simulators: from topological models to applications in real life problems.

Conferencia invitada. -- Qion 2019, WG2/WG3 Cost meeting, Carlton Tel-Aviv Hotel, 02-05 September 2019. -- https://www.qion19.org/
WAE$$_{-}$$RN: Integrating Wasserstein Autoencoder and Relational Network for Text Sequence

One challenge in Natural Language Processing (NLP) area is to learn semantic representation in different contexts. Recent works on pre-trained language model have received great attentions and have been proven as an effective technique. In spite of the success of pre-trained language model in many NLP tasks, the learned text representation only contains the correlation among the words in the sentence itself and ignores the implicit relationship between arbitrary tokens in the sequence. To address this problem, we focus on how to make our model effectively learn word representations that contain the relational information between any tokens of text sequences. In this paper, we propose to integrate the relational network(RN) into a Wasserstein autoencoder(WAE). Specifically, WAE and RN are used to better keep the semantic structurse and capture the relational information, respectively. Extensive experiments demonstrate that our proposed model achieves significant improvements over the traditional Seq2Seq baselines.
Implementation of a logo detection system based on deep learning strategies for media impact analysis in social networks

Nowadays, social networks are one of the principal focus of attention of millions of people all around the world. Companies are aware of this and try to extract from them valuable information to be applied in the design of a good marketing strategy.The objective of this thesis consists in developing a logo detector that is able to determine the location of any brand logo in an image or video. The main purpose is to determine the media impact of any company in the social media, although it could be useful for other applications such as copyright infraction detection. The developed system will be based on a deep learning strategy focused on object detection that will be combined with CutMix, a state-of-the-art training strategy that improves the learning process. The input of the object detector would be an image or frame from a video and the output, the location of every potential logo inside the image. The develop logo detection system will be tested to check the accuracy as a function of the size and distortion of the images.Finally, it is remarkable that most of the existing logo datasets are excessively small. And the few large ones contain weakly labelled and noisy images that are not suitable. Therefore, a carefully selection and potentially aggregation of databases would be also required.
Evaluating alternatives to native development for handheld computers

Selecting a suitable mobile application development framework is challenging. Multiple frameworks exist with respective strengths and weaknesses, and evaluations comparing the different frameworks ...
가상현실(VR)에 기반한 영어발음 학습콘텐츠 요구도

(Purpose) The purpose of this study is to understand the college students'' needs for the development of learning contents in English pronunciation education using virtual reality (VR). (Design/methodology/approach) The survey was conducted using a structured questionnaire for 281 college students in D University from January 3-10, 2020. The questionnaire consists of questions related to English learning status, awareness of VR based English pronunciation learning, educational contents and methods.(Findings) Among English learning contents, 80.2% of the students chose ‘travel’ for their preferred contents. The findings reveal that the students expected that VR-based English learning contents should be developed based on speaking and listening (72.2%), learners’ selective use (75.0%), consideration of the difficulty level according to the individual learner’s level (81.3%) and preference (77.9%). In addition, there was a significant difference in the subjective level of English competencies as the ''very good'' group showed high knowledge of VR, future utilization, and intention to participate in VR English education program (P <0.05).(Research implications or Originality) Therefore, the findings of this research suggest that English pronunciation learning contents using VR can be useful in English education when developed as a customized program reflecting the individual learner’s level.
Solist med storband

This project deals with the different aspects and problems that I associate with being a soloist with a big band, playing my own music. I put together a big band with some of my favorite musicians, ...
PENINGKATAN HASIL BELAJAR DALAM MATA PELAJARAN PKN MELALUI MODEL PEMBELAJARAN KOOPERATIF TIPE STUDENT FACILITATOR AND EXPLAINING DI KELAS IV SDN 08 KUMBAYAU

Based on Student Learning Outcomes of Class IV SDN 08 Kumbayau in PKN subjects it was found that Student Learning Outcomes in PKN subjects were still very low. The purpose of this study was to describe and obtain information about Improving Student Learning Outcomes in PKN subjects through the cooperative learning model type Student Facilitator and Explaining in Class IV SDN 08 Kumbayau. This research is a class action research. Research procedures in this study include planning, action, observation and reflection. This research consisted of two cycles with four meetings. The research subjects consisted of 18 students of Class IV SDN 08 Kumbayau. Research data were collected using Observation sheets. Data were analyzed using percentages.Based on the results of research and discussion that have been presented in the previous chapter, it can be concluded that it can be concluded that the model of demonstration learning can improve student learning outcomes in PKN subjects in Class IV SDN 08 Kumbayau. Student Learning Outcomes from cycle I to cycle II. Student learning outcomes in the first cycle was 68.89 (enough) increased to 77.78 (good) with an increase of 8.89 (good).
An Improved Deep Reinforcement Learning with Sparse Rewards

This paper presents an improved deep reinforcement learning which encourages an agent to explore unvisited states in an environment with sparse rewards. The improved method is based on an actor-critic approach. It uses some neglected observations from the background as the target output of supervised learning, providing the agent denser training signals to bootstrap reinforcement learning. Moreover, the improved method uses the prediction loss from supervised learning as feedback for the agent's exploration in the environment, called the label reward, to encourage the agent to explore unvisited states. Finally, the improved method constructs multiple neural networks to learn a policy by the Asynchronous Advantage Actor-Critic algorithm.
Konflik Batin Tokoh Utama Dalam Novel Drupadi Karya Seno Gumira Ajidarma : Kajian Psikologi Sastra dan Relevansi sebagai Pembelajaran Sastra di SMA

This study aims to describe 1) Seno Gumira Ajidarma sociohistorical background as the author of the Drupadi novel, 2) the structure that builds Seno Gumira Ajidarma Drupadi novel, 3) the inner conflict of the main characters in the Drupadi novel. – Seno Gumira Ajidarma Project with Literary Psychology review, and 4) its implementation in Seno Gumira Ajidarma People's Project novel by studying literature in high school. This research uses descriptive qualitative method with the object of research is the inner conflict of the main characters in the novel Drupadi Project. Data collection is carried out by using library, listening and note taking techniques. The validity of the data uses the theory triangulation technique. Data analysis technique is done by the heuristic and hermeneutic methods. The results of this study are (1) Seno Gumira Ajidarma, born in Boston, United States of America, Regency on June 19, 1958. Seno Gumira Ajidarma was raised in Yogyakarta. Seno Gumira Ajidarma published works in the form a collection of poetry, a collection of short stories, a collection of drama scripts, comics, novels, and essays (2) the structure of the novel Drupadi, among others, The theme is something that is fought over in a bad way will lead to revenge and violence, novel Drupadi this lift the suffering experienced by women during the Mahabarata. Story facts, a) the plot used is the forward plot, b) the main character is Drupadi, c) the setting in which this manuscript is the setting is located between the India, the time frame occurred from 1293-1500, the setting social India society because the story also takes place in rural areas in India. (3) inner conflict main characters of the Drupadi there are three types of inner conflict namely approach- approach conflict (approach-approach conflict) approach-approach conflict (approach -avoidance conflict) and conflict avoidance-avoidance conflict, (4) Relevant to learning in high school on KD 3.9 grade XII, the criteria for literary learning include three aspects namely language, psychology, and cultural background.
Implementasi Dan Analisa Security Auditing Menggunakan Open Source Software Dengan Framework Mitre Att&ck

Abstrak Security auditing merupakan proses pengumpulan dan evaluasi bukti-bukti untuk menentukan apakah sistem komputer yang digunakan telah dapat melindungi aset milik organisasi. Pada penelitian ini security auditing dilakukan berdasarkan analisa vulnerability dan threat agar dapat melihat hubungan yang terjadi antara vulnerability dan threat yang telah dilakukan pada aset IT tersebut. Pada penelitian ini objek yang digunakan yaitu vulnerable operating system (VulnOSv2) dengan tujuan untuk mengetahui vulnerability dan threat. Pada penilitian ini digunakan 10 walkthrough dengan tujuan dapat dilakukan analisis perbandingan pada masing masing walkthrough serta melihat efisiensi dari masing-masing tools yang digunakan. Eksperimen dilakukan dengan menggunakan framework MITRE ATT&CK dimana digunakan sebagai dasar untuk pengembangan model dan metodologi ancaman. Open source software OpenVAS dapat diterapkan guna melihat hasil kuantitatif yang berdasarkan scanning eskploitasi berupa vulnerability. Sedangkan secara kualitatif dengan menyusun model attack trees. Framework MITRE ATT&CK yang dibuat dapat mengakomodasi model attack trees yaitu sebesar 80%. Kata kunci : Security Auditing, Vulnerability, Threat, Risk, Framework MITRE ATT&CK Abstract Security auditing is the process of gathering and evaluating evidence to determine whether the computer system used has been able to protect the assets belonging to the organization. In this research, security auditing is conducted based on the analysis of vulnerability and threat in order to see the relationship that occurs between vulnerability and threats that have been carried out on these IT assets. In this study the object used is vulnerable operating system (VulnOSv2) with the aim to determine vulnerability and threat. In this research 10 walkthroughs are used with the aim that comparative analysis can be performed on each walkthrough and see the efficiency of each tool used. Experiments were carried out using the MITRE ATT&CK framework which is used as a basis for developing threat models and methodologies. Open source software OpenVAS can be applied to see quantitative results based on exploitation scanning in the form of vulnerability. Whereas arranging attack tree models the MITRE ATT&CK Framework created can accommodate attack tree models, which is 80%. Keywords : Security Auditing, Vulnerability, Threat, Risk, Framework MITRE ATT&CK
Optimal visual search based on a model of target detectability in natural images

To analyse visual systems, the concept of an ideal observer promises an optimal response for a given task. Bayesian ideal observers can provide optimal responses under uncertainty, if they are given the true distributions as input. In visual search tasks, prior studies have used signal to noise ratio (SNR) or psychophysics experiments to set the distributional parameters for simple targets on backgrounds with known patterns, however these methods do not easily translate to complex targets on natural scenes. Here, we develop a model of target detectability in natural images to estimate the parameters of target-present and target-absent distributions for a visual search task. We present a novel approach for approximating the foveated detectability of a known target in natural backgrounds based on biological aspects of human visual system. Our model considers both the uncertainty about target position and the visual system’s variability due to its reduced performance in the periphery compared to the fovea. Our automated prediction algorithm uses trained logistic regression as a post processing phase of a pre-trained deep neural network. Eye tracking data from 12 observers detecting targets on natural image backgrounds are used as ground truth to tune foveation parameters and evaluate the model, using cross-validation. Finally, the model of target detectability is used in a Bayesian ideal observer model of visual search, and compared to human search performance.
Catfishing: The lure of the law: Should catfishing be a crime?

Victims of online deception are often left heartbroken, bankrupt, destitute or even suicidal. While some predators face charges for fraud or extortion, many who commit these irreparable harms will never face any consequences. Is it time to criminalise catfishing?
Delta-STN: Efficient Bilevel Optimization for Neural Networks using  Structured Response Jacobians

Hyperparameter optimization of neural networks can be elegantly formulated as a bilevel optimization problem. While research on bilevel optimization of neural networks has been dominated by implicit differentiation and unrolling, hypernetworks such as Self-Tuning Networks (STNs) have recently gained traction due to their ability to amortize the optimization of the inner objective. In this paper, we diagnose several subtle pathologies in the training of STNs. Based on these observations, we propose the $\Delta$-STN, an improved hypernetwork architecture which stabilizes training and optimizes hyperparameters much more efficiently than STNs. The key idea is to focus on accurately approximating the best-response Jacobian rather than the full best-response function; we achieve this by reparameterizing the hypernetwork and linearizing the network around the current parameters. We demonstrate empirically that our $\Delta$-STN can tune regularization hyperparameters (e.g. weight decay, dropout, number of cutout holes) with higher accuracy, faster convergence, and improved stability compared to existing approaches.
Parallel Aes diffusion inter block diffusion at bit level and compression

Information is an intelligent data through which knowledgeable and usable things can be convicted or interpreted in a proper manner. With the advancement of technology, transmission of information ...