Reviewerly/exHarmony huggingface dataset:
Mixed Realities: a live collaborative musical performance

In the presented work, a live-rendered percussionist is transformed into a virtual game character and performs a piece along digital avatars created from recordings (audio and motion-capture) of other members of an ensemble, while audience members can observe the collaborative performance through VR headsets. To create a cohesive and compelling result, the auditory expectations of the listeners need to be considered in terms of acoustic integrity between real and virtual sources and spatial impression of each avatar performer. This paper presents an overview of the workflow and motivations behind this pilot experiment of a novel musical experience, laying down the foundations for future subjective studies into collaborative music performances using virtual and augmented reality headsets. Particular focus is given to the technical challenges concerning the audio material, the perspectives of each participant role, and the qualitative impressions of musicians and audience.
High Throughput Low Complexity and Low Power ePiBM RS Decoder Using Fractional Folding

This brief proposes a novel generalized Fractional Folding (FF) architecture for digital signal processing integrated circuits. With this new structure, a Fractional Folding based enhanced Parallel Inversionless Berlekamp-Massey (FF-ePIBM) Reed-Solomon Decoder is presented of which the number of processing element (PE) can be reduced to only one, resulting in ultra-low hardware complexity. The FF-ePIBM VLSI architecture can greatly reduce the hardware cost by about 60% compare to the fully expanded parallel ePIBM architecture. With FF-ePIBM architecture, syndrome calculation (SC) block and Chien search & error evaluation (CSEE) block are able to operate at a lower frequency resulting in about 14.8% power saving. A polyphase clock signal is needed in order to achieve fractional folding function according to specific fractional-factor. It is generated from Delay Locked Loop (DLL) at little or no extra cost in different SoCs. To maximize the throughput of decoder, pipelined architecture is adopted to optimize critical path delay. The RS (255, 239) decoder with FF-ePIBM architecture is finally implemented with 40nm CMOS technology. The synthesized results demonstrate that the decoder has a gate count of 12.9k and can operate at 3.1GHz to achieve a highest throughput of 24.8Gb/s and a best TSNT FoM value of 592 to this date.
PELATIHAN PEMBUATAN VIDEO PEMBELAJARAN DI TK. AL-JABBAR BLIMBING KOTA MALANG

The targets of community service activities are the teachers or educators of Malang City's AlJabbar Kindergarten (TK), and other private kindergartens around them. The selection of private Al-Jabbar Kindergarten teachers is because the existing facilities of the school are inadequate, so there is a need for learning media assistance and enhancement of the quality of creative teachers in the learning process. This activity aims to help improve the quality of the learning process by increasing the ability of teachers in this school, so that learning is better and more enjoyable. PKM activities include: Introductory material, Learning media demo, Provision of Materials, practical training in making instructional media, Planning learning media according to topic, making instructional media according to plan, discussion and evaluation of learning media and finally improvement in making instructional media..
Persepsi Mahasiswa Tentang Penggunaan Web Design sebagai Model Pembelajaran Jarak Jauh Selama Pandemi di Perguruan Tinggi Aceh Barat

Based on data from the Central Statistics Agency (BPS), especially in Aceh, it was recorded that 4 thousand children were not able to effectively absorb material from teaching staff during the pandemic period (BPS Aceh, 2020). Therefore, the teaching staff needs to pay attention to the development of creative innovative distance learning models so as to increase the interest of students to keep interacting throughout the lesson hours. One method of distance learning that is believed to be able to increase student interest in learning is a web design designed by the teacher to be as attractive as possible so that students can easily access and study learning materials. The purpose of this study was to see the effectiveness of the Development of Distance Learning Models during the Pandemic with a Life Skills-Based Web Design Approach to i-students in West Aceh District. The subjects of this research are university students in West Aceh, namely Teuku Umar University students, STAIN Dirundeng and STIKIP Bina Bangsa Meulaboh. Participants were selected by purposive sampling so that there were 5 students from each campus. The results showed that most partisipants from three Universities in Aceh Barat responded positively to the use of Web Design as Distance Learning Method. Besides, the result from interview with them, there were four obstacles in distance learning, which are (1) the insufficient knowledge of technologi, (2) Internet signal problem, (3) lack of financial to get the internet quota, anda lastly, (4) unsatisfied material understanding from lecturer because of virtual learning.Keywords: Disctance Learning; Web Design Method
DEVELOPING INSTRUCTIONAL DESIGN FOR TEACHING WRITING PROCEDURAL TEXT USING PROJECT BASED LEARNING

This research was aimed to develop an Intructional design in teaching procedural text using project based learning. The instructional design assisted for teaching writing for ninth grade students at SMP Negeri 2 Pontianak. This research applied development research and ADD procedure. On the analysis stage the researcher found the fundamental problems and needs of the students as well as the teacher expectation of writing material. On the designing and developing stage, the researcher collected the sources that needed and developed the instructional design. After the product assessed by the material expert, the instructional design considered as valid and applicable to use. The researcher hope that, this product can be applied in the classroom. As for the future research, the researcher suggested to conduct the instructional design based on the needs of the students. Drawing a clear design is needed to lead a good development of product.
[Interpolation Algorithm for Motion Vector Field of CTA Image and Accelerated Implementation Based on Uniform Grid and Multi-level B-spline].

In order to solve the problems of slow operation speed and low registration accuracy of thin plate spline (TPS) interpolation method for motion vector field in coronary computed tomography angiography (CTA), a multi-level B-spline interpolation method (MBS) with uniform grid is proposed. On the one hand, the interpolation method used local B-spline to refine the sparse mesh layer by layer in a multiscale way to improve the accuracy of registration. On the other hand, it used the splitting matrix method to interpolate the motion vector field, greatly reducing the operation time of interpolation. The experimental results show that the proposed method can be used for CTA image registration efficiently.
Movie Recommendation System

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Dilated Fully Convolutional Neural Network for Depth Estimation from a Single Image

Depth prediction plays a key role in understanding a 3D scene.Several techniques have been developed throughout the years, among which Convolutional Neural Network has recently achieved state-of-the-art performance on estimating depth from a single image.However, traditional CNNs suffer from the lower resolution and information loss caused by the pooling layers.And oversized parameters generated from fully connected layers often lead to a exploded memory usage problem.In this paper, we present an advanced Dilated Fully Convolutional Neural Network to address the deficiencies.Taking advantages of the exponential expansion of the receptive field in dilated convolutions, our model can minimize the loss of resolution.It also reduces the amount of parameters significantly by replacing the fully connected layers with the fully convolutional layers.We show experimentally on NYU Depth V2 datasets that the depth prediction obtained from our model is considerably closer to ground truth than that from traditional CNNs techniques.
Synergy of Accreditation and CAE Designation

One of the impediments to applying for the NSA/DHS Center of Academic Excellence in Cyber Defense designation is the fear that it will require a great change to the curriculum or may negatively impact international functional accreditations. This paper provides lessons learned while preparing to apply for this designation and enhancing our international ABET (computer science) and AACSB (business) accreditations. We found synergy between the new cybersecurity requirements for accreditation and CAE designation. Additional benefits of CAE designation include standards which help design, build, market and assess strong, well-defined cybersecurity programs in both computer science and business, each of which caters to a different audience of students and future employers. Finally, the CAE designation requires collaboration inside and outside the University, encouraging an active outreach to other programs. All of these benefits work in concert with the ABET and AACSB accreditations, which explicitly require an internationally recognized curriculum that is taught by experts in their field and regularly assessed.
End-to-End Deep Learning-Based Human Activity Recognition Using Channel State Information

The automatic recognition of human activities in the house using Channel State Information (CSI) has received wide attention due to the potential use of wide range of intelligent services. Two-dimensional Convolutional Neural Network (2D-CNN) is one of the most popular approaches for human activity recognition (HAR). This method first applies signal transform to convert a time-series CSI signal into a 2D image, and then uses the image to train a complex 2D-CNN model. In this paper we will present simple deep neural networks including multi-layer perceptron (MLP) and one-dimensional Convolutional Neural Network (1D-CNN) for HAR. Our proposed networks are fully end-to-end automatic learning from feature extraction/selection and classification, and do not require extra signal transform and denoising. Experimental results indicate that the proposed networks not only achieve much better recognition performance but reduces the network complexity significantly, as compared to the existing methods.
LibGuides: Sol Plaatje University Library and Information Services General Guide: Training videos

Welcome to your SPU LIS general portal where you can find links to our electronic databases, other library resources and open resources.
Reserve and collect a library item

Currently you cannot reserve library items online through the library catalogue, but only as part of the Reserve and Collect Service.
Image super-resolution via deep residual network

Recently, convolution neural network (CNN) has been widely used in single image super-resolution (SR). However, the traditional network structure has the problems of fewer convolution layers and slow convergence speed. In this paper, an image super-resolution method based on deep residual network is proposed. Through the deepening of the network structure, more receptive fields are obtained. Thus, more pixel information is utilized to improve the reconstruction accuracy of the model. The feature extraction process is carried out directly in low resolution space, and the images are sampled by shuffling the pixels at the end of the network. The learning method combining global residual and local residual is used to improve the convergence speed of the network while recovering the high-frequency details of the images. In order to make full use of image feature information, feature maps extracted from different residual blocks are fused. In addition, parametric rectified linear unit (PReLU) is used as the activation function, and the Adam optimization method is used to further improve the reconstruction effect. The experimental results of benchmark datasets show that the proposed method is superior to other methods in subjective visual effects and objective evaluation indicators.
Theoretical Models of Galaxy Formation – East versus West

Two models of galaxy formation were being investigated simultaneously on the 1970’s. The bottom-up model was championed by Peebles, and the top-down model by Zeldovich. At first, dark matter was not part of either model, but this effort to explain the origin of galaxies eventually stalled for both models the because the temperature fluctuations in the cosmic background radiation are too small to accommodate galaxy formation from baryons alone. At first massive neutrinos were introduced as dark matter, and when this failed to word, cold dark matter (CDM) was introduced. CDM forms early halos, and then baryons eventually fall into these halos. The first CDM computer models of galaxy formation were introduced by Melott and Shandarin and later developed by the “Gang of Four” (White, Davis, Efstathiou and Frenk). Eventually, the top-down and bottom-up models gracefully merged, and the concept of “biasing” became part of the final model.
Library: Amberton University Library: Welcome to the Library

An online learning wayport that assembles and distributes information resources and learning experiences to the faculty and students of Amberton University.
Experiments with integer vectors

The algorithm described in [ 1 ], [ 2 ] and [ 3 ] is originally intended for integer vectors. Therefore, the programming language Python is well suited to represent large integers. In the following two Python source codes „EightPoints03.txt“ and „EightPoints03-graph.txt“ an example is discribed. The algorithm is derived exclusively from position and displacement vectors. In this example eight points are pairwise coupled so that four bivectors emerge. Within the bivectors the points are displaced by the step width h. The bivectors are coupled by charges. For the displacement step width pull caused by the charges shall apply 1 << pull << h.This is described by the reciprocal coupling factor reci: h = reci * pull.If one chooses reci close to 1, the coupling is so strong that chaos can be caused. If reci >> 100 is chosen, the coupling between the bivectors is very weak, so that the interactions are very slow.[ 1 ] https://opus4.kobv.de/opus4-ohm/frontdoor/index/index/docId/34[ 2 ] https://opus4.kobv.de/opus4-ohm/frontdoor/index/index/docId/126[ 3 ] https://opus4.kobv.de/opus4-ohm/frontdoor/index/index/docId/253
What motivates teenagers to comply with security guidelines

We examined factors that inspire teenagers to comply with cyber security guidelines. We used protection motivation theory (PMT), and extended the model to include personal norms and normative beliefs. For teenage computer users, believing they are susceptible to hacking or that the consequences of being hacked would be severe, had no bearing on their password choices. This is an interesting finding highlighting a potential difference between adults and teenagers. We found personal norms is a better predictor of teenagers’ security behaviour than PMT’s threat perceptions. This is an important finding which opens new avenues for future research, particularly in explaining teenagers’ security behaviour. This study contributes to finding ways to improve security practices at an early age. To the best of our knowledge this is the first password security study that applies PMT to examine security behaviours in teenagers.
Implementation Model of Cloud Computing for Education Intuitions with Respect to Core Issues

Abstract. History of cloud computing is rooted back in 1943 with the “Z3” the first fully automatic electromechanical computer.  EIANC the first general purpose computer was developed in 1945. Cloud computing concept started in 1950s with the evolution of mainframe computing. Cloud computing has been penetrating in various organization, but a universally acceptable model for educational institutions is not available. Literature review is carried out for study of cloud and its applications in IT revealed that there exist various issues in the implementation of cloud solutions in universities/colleges. We made a study on data collected through a questionnaire from various institutions of technical education, analyzed, interpreted and propose a suitable model to be adopted, which address the core issues refraining the use  of cloud in these intuitions. Keywords: VM, SaaS, PaaS, IaaS, Cloud Cite this Article Nilam Choudhary, Baldev Singh. Implementation Model of Cloud Computing for Education Institutions with Respect to Core Issues. Recent Trends in Parallel Computing. 2018; 5(3): 30–36p.
AI Model Lifecycle Management: Systematic Mapping Study and Solution for AI Democratisation

The development of artificial intelligence (AI) has made various industries eager to realise and obtain the benefits of AI. There is an increasing amount of research surrounding AI, most of which is centred on the development of new AI algorithms and techniques, thereby, however, ignoring an increasing set of practical problems related to AI mode lifecycle management, examples include versioning control of the data and models, difficulties in model deployment, transparency, model reproducibility, fairness and balance in data, and ethics. In contrast to this extensive list, research on the AI model lifecycle management is limited, and there is currently no comprehensive study. To address this gap, we researched the life cycle management of AI models. The research consisted of two parts. First, we conducted a systematic mapping study, which consists of the classification and counting of published papers in this field. By summarising the current situation of this field through quantitative and qualitative research, we obtained an overview, identified research gaps, and provided suggestions for future research. We then selected one of the specific themes, AI democratisation. Using this theme, we researched relevant literature, highlighted the importance of model documentation and the research gap, carried out research on the existing model documentation framework, improved the current framework, and introduced a solution for promoting AI democratisation. Specifically, we proposed a tool to automatically generate model documentation. Finally, we conducted a user study on the tool as a means of gathering suggestions for future improvements. Purpose: Improve the life cycle management of AI from a theoretical and practical perspective through conducting a comprehensive study of the life cycle management of artificial intelligence models; a solution to a specific topic/research gap (i,e., the democratisation of AI). Method: We carried out systematic mapping research on the life cycle management of AI models. Regarding AI democratisation, we researched literature pertaining to the democratisation of existing AI, compared with existing solutions, and improved AI from the perspective of generating model documents. Results and Conclusion: The systemic map was obtained by categorising and counting related publications, improving the existing model document framework, and proposing a solution to automatically generate model documents, thereby improving AI democratisation.
Towards Quantum One-Time Memories from Stateless Hardware

A central tenet of theoretical cryptography is the study of the minimal assumptions required to implement a given cryptographic primitive. One such primitive is the one-time memory (OTM), introduced by Goldwasser, Kalai, and Rothblum [CRYPTO 2008], which is a classical functionality modeled after a non-interactive 1-out-of-2 oblivious transfer, and which is complete for one-time classical and quantum programs. It is known that secure OTMs do not exist in the standard model in both the classical and quantum settings. Here, we propose a scheme for using quantum information, together with the assumption of stateless (i.e., reusable) hardware tokens, to build statistically secure OTMs. Via the semidefinite programming-based quantum games framework of Gutoski and Watrous [STOC 2007], we prove security for a malicious receiver, against a linear number of adaptive queries to the token, in the quantum universal composability framework, but leave open the question of security against a polynomial amount of queries. Compared to alternative schemes derived from the literature on quantum money, our scheme is technologically simple since it is of the prepare-and-measure type. We also show our scheme is tight according to two scenarios.
LibGuides: A Guide for Reluctant Teen Readers: Additional Resources

This guide is a resource for teens (ages 13-18) who may be reluctant to read, who struggle to enjoy books, or who need a starting place for rekindling their previous love for reading.
Complicações cardiovasculares em pacientes com Diabetes Mellitus Tipo 2

Objective: This article sought to conduct a review on microvascular and macrovascular complications in patients with Type 2 Diabetes Mellitus (DMT2), as well as to clarify the behavior of the human body in the face of these changes and the importance of early diagnosis and treatment for a better quality of life of these individuals. Bibliographic review: DMT2 is an alarmingly growing disease, which mainly contributes to the development of cardiovascular complications.&nbsp; The complications of DMT2 include Diabetic Renal Disease, Diabetic Retinopathy, Diabetic Neuropathy and Sexual Dysfunction, these being microvascular. It is also observed the occurrence of Heart Failure, Stroke and Acute Myocardial Infarction as the main macrovascular complications. These alterations are directly related to Systemic Arterial Hypertension, Dyslipidemias and Obesity, causing a high lethality mainly when related to heart failure in these individuals. Final considerations: It was verified in this work that the impairment of quality of life by DMT2 reduces the life expectancy of individuals when compared to non-diabetics.
Big Data, institucionalidade da informação e Ciência da Informação: elementos para uma reflexão

Objective: This article aims to map and analyze authors and works that deal with the Big Data theme in the field of Information Science.Method: This is a qualitative, descriptive and bibliographic research in which literature review used data mapped in previously selected national and international databases.Results: The concepts of Big Data in CI worked on in this paper demonstrate, while presenting a polysemic potential, the absence of explicit divergences regarding the conceptualization of the phenomenon. It was also observed that the research on the institutionalization of information - transformation of digital object into information, that is, into something meaningful - can be a useful way to reflect on the Big Data phenomenon.Conclusions: The Big Data phenomenon is characterized as a phenomenon considered from its technological characteristics or the way such technologies have been used. Even if preliminarily, it was observed that both approaches do not have marked differences as they can be observed concurrently in different studies.