Reviewerly/exHarmony huggingface dataset:
Introducing strauss: A Flexible Sonification Python Package

We introduce strauss (Sonification Tools and Resources for Analysis Using Sound Synthesis) a modular, self-contained and flexible Python sonification package, operating in a free and open source (FOSS) capacity. strauss is intended to be a flexible tool suitable for both scientific data exploration and analysis as well as for producing sonifications that are suitable for public outreach and artistic contexts. We explain the motivations behind strauss, and how these lead to our design choices. We also describe the basic code structure and concepts. We then present output sonification examples, specifically: (1) multiple representations of univariate data (i.e., single data series) for data exploration; (2) how multi-variate data can be mapped onto sound to help interpret how those data variables are related and; (3) a full spatial audio example for immersive Virtual Reality. We summarise, alluding to some of the future functionality as strauss development accelerates.
Review of joint text editing algorithms Conflict-free Replicated Data Types (CRDT)

Analysing and selecting algorithms for collaborative text editing, especially implementing conflict-free replicated data types, is critical to understanding how modern systems can achieve real-time collaboration while ensuring data integrity. The purpose of the study is to review various collaborative editing algorithms and conduct a comparative analysis to understand their advantages, disadvantages, and applications. Statistical methods, methods for analysing algorithms and their use in real-world scenarios are used. The study results showed that the use of collaborative text editing algorithms contributes to solving important tasks and challenges in the modern world of information technology. Collaborative editing algorithms are determined to facilitate realtime communication and information exchange. This is especially important in the context of remote work and communication, which have become the standard for many organisations. Collaborative text editing is widely used in various fields and industries where teamwork, real-time collaboration, and document sharing are essential, such as scientific research, education, software development, book and manuscript editing, legal cooperation, contract draughting, medical reports, etc. In addition, using optimised collaborative editing algorithms helps reduce the time required to process data and create text materials. Collaborative editing algorithms have a wide range of applications in research, business, and education. They allow teams and individual users to solve problems more efficiently and work together on projects. The ability to use the results obtained in practical activities will allow using algorithms for joint text editing for further innovation and development of information technologies, which will allow working together and exchanging information with the whole world in real-time
STRUCTURAL ANALYSIS, PETROGRAPHIC STUDY AND GEOCHEMICAL ASSESSMENT OF PAN-AFRICAN GRANITOID, GUSAU SHEET 54SE NORTHWEST NIGERIA

The study area is underlain by migmatite-gneiss quartzite rock suits with infolding mica schist which is intruded by batholitic Pan-African granitoids. Petrographic studies revealed quartz, orthoclase, hornblende and biotite as major minerals which are common to all members of rock units. The geochemical result of gneissic rock shows SiO2 content that range between 77.04%.wt to 80%.wt while mica schist depicts SiO2 content of 74.42 to 77.42%.wt. this implies silicious protolith for the both rock units. On the discrimination diagram gneiss and mica schist plot mainly in High-K calc-alkaline to calc-alkaline fields. Whereas, bivariate diagram of TiO2 versus SiO2 revealed that both gneissic rock and mica schist have sedimentary progenitors. High Rb, La and Th and low Nb, Sr, and Ti values shown by both gneiss and mica schist are compatible with typical crustal melts and suggest evolution from partial melting of crustal materials. The Pan-African granitoids has similar geochemical relationships. Geochemical studies shows that the rock units have limited variation in their major element compositions and give a decrease in CaO wt. %, and increasing Ba/Sr, Zr/Y ratios, K2O wt. % with increasing silica. The rocks are distinctly peraluminous, calc-alkaline as they plot in the High-K calc-alkaline and calc-alkaline, syn-collision fields on various discrimination diagrams. The characteristics suggest that the Basement rocks of the study area were formed from the fractional crystallization of a calc-alkaline magma in a syn- collision tectonic terrain.
Imaging Spectroscopy and Machine Learning for Earth Science

Imaging spectroscopy, or hyperspectral imaging, will form a core part of NASA’s Earth System Observatory’s, which aims to understand and monitor Earth processes. We will discuss the challenges and opportunities of processing these rich datasets on a global scale.
Silicon Photonics for AI Computing and Communication

We will present recent developments in silicon photonics for AI workloads. Photonic analog compute systems accelerate matrix multiplication operations, while highly scaled photonic interconnects improve memory bandwidth and enable larger and more flexible networks.
Visible Photonics for Scaling Beam Delivery to Trapped Ion Quantum Computers

Beam delivery for trapped ion quantum computing systems requires fine control of beam pointing, amplitude, phase, frequency, and pulse timing. I will discuss challenges scaling these systems and describe why visible integrated photonics offers promise.
Data-Driven Photography

This talk is about the importance of training and inference data for photography applications - how additional input observations can be harnessed and reinforced with generic data priors from ML models trained on large-scale datasets.
Penerepan Metode Bermain Peran (Role Play) Dalam Meningkatkan Minat Belajar Siswa Pada Mata Pelajaran IPS Kelas IV DI SDN 173249 Sibulan- Bulan

In an educational context, student interest in learning is very important, because high interest will motivate students to learn more enthusiastically and have a positive impact on achieving learning outcomes Role playing is a learning strategy that involves students in imaginary situations where they take on certain roles or characters. related to Social Studies (Social Studies) class IV. This study uses a Classroom Action Research (CAR) approach. The data collection techniques used in this study were observation, tests, and documentation. The research instruments were teacher observation sheets, student observation sheets, and evaluation question sheets.
Policing the Onion Router (Tor) crypto-markets on the dark web: An analysis of South African investigatory powers

Emerging financial technology (fintech), such as cryptocurrencies and privacy-enhancing technology (pets) such as the Onion Router (Tor), enable varying levels of anonymity or pseudonymity based on underlying encryption algorithms. These technologies are increasingly exploited by cybercriminals for nefarious purposes on the dark web. This has resulted in the so-called tor crypto-markets that facilitate ‘digital organised crime.’ Thus, albeit not inherently criminogenic, encryption constitutes a barrier to criminal investigation. This article discusses two specific methods that police use to investigate and prosecute criminals operating on the dark web, through the use of hacking tools in the context of: (1) online undercover cybersurveillance operations; and (2) remote search and seizure. These methods differ in both scope and complexity and, importantly, bear distinct legal, technical, and ethical consequences that have yet to confront South African courts. As a result, these methods, in the context of dark web investigations, have not previously been considered in South African literature, but have received significant analysis in the United States, the Netherlands, and Australia. These methods will be discussed in the context of South African investigatory powers in order to determine whether there is a legal basis for its operation.
Mutual-Information Regularization in Markov Decision Processes and Actor-Critic Learning.

Cumulative entropy regularization introduces a regulatory signal to the reinforcement learning (RL) problem that encourages policies with high-entropy actions, which is equivalent to enforcing small deviations from a uniform reference marginal policy. This has been shown to improve exploration and robustness, and it tackles the value overestimation problem. It also leads to a significant performance increase in tabular and high-dimensional settings, as demonstrated via algorithms such as soft Q-learning (SQL) and soft actor-critic (SAC). Cumulative entropy regularization has been extended to optimize over the reference marginal policy instead of keeping it fixed, yielding a regularization that minimizes the mutual information between states and actions. While this has been initially proposed for Markov Decision Processes (MDPs) in tabular settings, it was recently shown that a similar principle leads to significant improvements over vanilla SQL in RL for high-dimensional domains with discrete actions and function approximators. Here, we follow the motivation of mutual-information regularization from an inference perspective and theoretically analyze the corresponding Bellman operator. Inspired by this Bellman operator, we devise a novel mutual-information regularized actor-critic learning (MIRACLE) algorithm for continuous action spaces that optimizes over the reference marginal policy. We empirically validate MIRACLE in the Mujoco robotics simulator, where we demonstrate that it can compete with contemporary RL methods. Most notably, it can improve over the model-free state-of-the-art SAC algorithm which implicitly assumes a fixed reference policy.
SITHCon: A neural network robust to variations in input scaling on the time dimension.

In machine learning, convolutional neural networks (CNNs) have been extremely influential in both computer vision and in recognizing patterns extended over time. In computer vision, part of the flexibility arises from the use of max-pooling operations over the convolutions to attain translation invariance. In the mammalian brain, neural representations of time use a set of temporal basis functions. Critically, these basis functions appear to be arranged in a geometric series such that the basis set is evenly distributed over logarithmic time. This paper introduces a Scale-Invariant Temporal History Convolution network (SITHCon) that uses a logarithmically-distributed temporal memory. A max-pool over a logarithmically-distributed temporal memory results in scale-invariance in time. We compare performance of SITHCon to a Temporal Convolution Network (TCN) and demonstrate that, although both networks can learn classification and regression problems on both univariate and multivariate time series $f(t)$, only SITHCon has the property that it generalizes without retraining to rescaled versions of the input $f(at)$. This property, inspired by findings from neuroscience and psychology, could lead to large-scale networks with dramatically different capabilities, including faster training and greater generalizability, even with significantly fewer free parameters.
An IoT Transport Architecture for Passenger Counting: A Real Implementation

A smart urban mobility considers the technological-based development in transport systems, services and their use to improve the movement of people and goods inter or intra-cities. Cities increasingly face problems caused by traffic and need to find solutions to improve mobility and to reduce congestion and pollution. In this paper, we present a Passenger Counting Scheme into buses. Embedded counting algorithms based on Computer Vision are proposed to count passenger arrivals and departures in real time. Experiments in a real scenario expose that the proposed scheme achieved a high percentage of success in passenger count.
Some considerations regarding the use of protective lenses in computer activities

The 11th International Conference on Information Science and Information Literacy – ICISIL 2021 – will take place in Brașov, Romania, on the 11th and 12th of March, 2021. The conference will be organized by Transilvania University of Brasov, Lucian Blaga University of Sibiu, with the support of The Public Library of Brașov County and MB Think Tank. ICISIL 2021 will focus on: The Role of Information in Services Provided to Innovative Users. ICISIL 2021 will bring together professionals, academic staff, including doctoral students, with a focus on Information Sciences, along with policy-makers and stakeholders. The conference fosters an inter-disciplinary exchange of knowledge. Sessions include contributed papers, keynote presentations and panel discussions. We support PhD students in the field through reduced registration fees. In addition, a PhD workshop will be held in the morning of 12 March 2021, as part of the ICISIL 2021 annual conference, at no extra cost for all registered students. Moreover, ICISIL 2021 will host a workshop on Innovative Technologies, focusing on 3D printing. Please submit your article via Editorial Manager Editorial Manager ABSTRACTING & INDEXING 11th International Conference on Information Science and Information Literacy is covered by the
Is 2D Heatmap Representation Even Necessary for Human Pose Estimation

The 2D heatmap representation has dominated human pose estimation for years due to its high performance. However, heatmap-based approaches have some drawbacks: 1) The performance drops dramatically in the low-resolution images, which are frequently encountered in real-world scenarios. 2) To improve the localization precision, multiple upsample layers may be needed to recover the feature map resolution from low to high, which are computationally expensive. 3) Extra coordinate refinement is usually necessary to reduce the quantization error of downscaled heatmaps. To address these issues, we propose a \textbf{Sim}ple yet promising \textbf{D}isentangled \textbf{R}epresentation for keypoint coordinate (\emph{SimDR}), reformulating human keypoint localization as a task of classification. In detail, we propose to disentangle the representation of horizontal and vertical coordinates for keypoint location, leading to a more efficient scheme without extra upsampling and refinement. Comprehensive experiments conducted over COCO dataset show that the proposed \emph{heatmap-free} methods outperform \emph{heatmap-based} counterparts in all tested input resolutions, especially in lower resolutions by a large margin. Code will be made publicly available at \url{this https URL}.
WEIGHT BASED DEDUPLICATION FOR MINIMIZING DATA REPLICATION IN PUBLIC CLOUD STORAGE

The approach to minimize data replication in cloud storage is one of the challenging issues to process text data. The amount of digital data has been increasing exponentially. There is a need to reduce the amount of storage space by storing the data efficiently. In cloud storage environment, the data replication provides high availability with fault tolerance system. An effective approach of deduplication system using a weight based method is proposed at the target level in order to reduce the storage space in cloud. Storage space can be efficiently utilized by removing the unpopular files from the secondary servers. Target level consumes less processing power than Source level deduplication. Input text documents are stored into Dropbox cloud. The Term Frequency (TF) and Named Entity Recognition (NER) of the documents are found. The text features found are stored in database using MySQL. After storing features in database, fresh text documents are collected to find popular and unpopular files. TF and NER are found for the freshly collected text documents and duplicate features are removed to compare with the features stored in the database. On comparison, relevant text documents are listed. After listing text documents, document frequency, document weight and threshold factor are found. Depending on threshold factor, the popular and unpopular files are detected. The popular files are replicated in all the storage nodes to achieve availability. Before deduplication, the storage space occupied in the Dropbox cloud is 8.09MB. After deduplication, the unpopular files are removed from secondary storage nodes and the storage space occupied in the Dropbox cloud is 4.82MB. Finally, data replications are minimized and 45.6% of the cloud storage space is efficiently saved by applying weight based deduplication.
3D printing techniques in making custom eyeglasses frames

The 11th International Conference on Information Science and Information Literacy – ICISIL 2021 – will take place in Brașov, Romania, on the 11th and 12th of March, 2021. The conference will be organized by Transilvania University of Brasov, Lucian Blaga University of Sibiu, with the support of The Public Library of Brașov County and MB Think Tank. ICISIL 2021 will focus on: The Role of Information in Services Provided to Innovative Users. ICISIL 2021 will bring together professionals, academic staff, including doctoral students, with a focus on Information Sciences, along with policy-makers and stakeholders. The conference fosters an inter-disciplinary exchange of knowledge. Sessions include contributed papers, keynote presentations and panel discussions. We support PhD students in the field through reduced registration fees. In addition, a PhD workshop will be held in the morning of 12 March 2021, as part of the ICISIL 2021 annual conference, at no extra cost for all registered students. Moreover, ICISIL 2021 will host a workshop on Innovative Technologies, focusing on 3D printing. Please submit your article via Editorial Manager Editorial Manager ABSTRACTING & INDEXING 11th International Conference on Information Science and Information Literacy is covered by the
Effects of Smartphone Overuse on Academic Delay Behavior by Some Dental Hygiene Students: The Mediating and Moderating Effects of Sleep Disorder Characteristics

Objectives: This study examines the mediating and moderating effects of characteristics of sleep disorders on the impact of smartphone overuse on academic delay in dental hygiene students. Methods: A survey was conducted from October 19 to November 27, 2020, targeting 164 dental hygiene students in Busan and Daejeon. The analysis method used the SPSS 26.0 program. Results: As a result of analyzing the characteristics of sleep disorders, it was found that as the characteristics of sleep disorders increased, the influence of excessive use of smartphones on academic delay behavior increased (p&lt;.001). Sleep disorder characteristics were found to partially mediate smartphone overuse and academic delay behavior, indicating that the sleep disorder characteristics were significant. Conclusions: This study explores the relationship between smartphone use and the sleeping habits of dental hygiene students and the impact of these factors on academic performance
Design of Trust Identification System for Cloud Services

Cloud computing is merging into every aspect of our information exchange including our personal information, business environment and other environments along with numerous security and trust challenges. With rapidly developing cloud utilisation, the range of security issues and trust challenges also increases exponentially. Hence an efficient trust identification system (TIS) is needed to identify the region of trusted cloud service providers (CSPs) for a particular service. In this paper, a novel trust identification technique is proposed based on linear programming using objective functions which can smartly spot the region of trust from the CSP pool. In this system, the cluster of trusted CSP is defined and the remaining CSPs are not recommended to the cloud customer (CC). The internet architecture is a wide area network with interoperability, scalability and durability. The analysis of the proposed system proves to be efficient in terms of accuracy and time complexity.
Why We Need an Interdisciplinary View in Information Retrieval

The 11th International Conference on Information Science and Information Literacy – ICISIL 2021 – will take place in Brașov, Romania, on the 11th and 12th of March, 2021. The conference will be organized by Transilvania University of Brasov, Lucian Blaga University of Sibiu, with the support of The Public Library of Brașov County and MB Think Tank. ICISIL 2021 will focus on: The Role of Information in Services Provided to Innovative Users. ICISIL 2021 will bring together professionals, academic staff, including doctoral students, with a focus on Information Sciences, along with policy-makers and stakeholders. The conference fosters an inter-disciplinary exchange of knowledge. Sessions include contributed papers, keynote presentations and panel discussions. We support PhD students in the field through reduced registration fees. In addition, a PhD workshop will be held in the morning of 12 March 2021, as part of the ICISIL 2021 annual conference, at no extra cost for all registered students. Moreover, ICISIL 2021 will host a workshop on Innovative Technologies, focusing on 3D printing. Please submit your article via Editorial Manager Editorial Manager ABSTRACTING & INDEXING 11th International Conference on Information Science and Information Literacy is covered by the
Roughcast analysis as a new method of environmental research

The aim of this study is to show purpose of roughcast analysis as a new useful tool for research of the condition of the environment. Samples of roughcast were collected from buildings in 6 different cities of Europe (Cracow, Lublin, Warsaw, Lviv, Monchegorsk and Murmansk) and their compositions were examined with scanning electron microscope, ICP-OAS and ASA methods. Also, binocular magnifier was used. The samples were investigated for heavy metals presence. The result shows that despite the deposition of particles is bigger on horizontal surface, the vertical layer of roughcast accumulate significant amounts of impurities and heavy metals. The composition and content of metals differ accordingly to automotive traffic nowadays and in the past, existence of road hubs, industrial districts and historical manufactures. Samples from Cracow show high content of non-ferrous metals and nickel, whereas content of copper was significantly higher in Monchegorsk. In Lublin and Lviv, their agricultural past contributed to significantly lower heavy metal content Determination of heavy metals contents in roughcast can be used to evaluate anthropogenic impact in the cities through the years and to help to protect cities’ population from negative consequences of living in urban areas.
Assistive systems for subjects with low vision

The 11th International Conference on Information Science and Information Literacy – ICISIL 2021 – will take place in Brașov, Romania, on the 11th and 12th of March, 2021. The conference will be organized by Transilvania University of Brasov, Lucian Blaga University of Sibiu, with the support of The Public Library of Brașov County and MB Think Tank. ICISIL 2021 will focus on: The Role of Information in Services Provided to Innovative Users. ICISIL 2021 will bring together professionals, academic staff, including doctoral students, with a focus on Information Sciences, along with policy-makers and stakeholders. The conference fosters an inter-disciplinary exchange of knowledge. Sessions include contributed papers, keynote presentations and panel discussions. We support PhD students in the field through reduced registration fees. In addition, a PhD workshop will be held in the morning of 12 March 2021, as part of the ICISIL 2021 annual conference, at no extra cost for all registered students. Moreover, ICISIL 2021 will host a workshop on Innovative Technologies, focusing on 3D printing. Please submit your article via Editorial Manager Editorial Manager ABSTRACTING & INDEXING 11th International Conference on Information Science and Information Literacy is covered by the