Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of membrane bio-reactor technology in alleviating South Africa's imminent water crisis

4 Table of contents . 5 List of tables . 8 List of figures . 9 Chapter One: Introduction to the study . 10 1.1 Background to the study . 10 1.2 The research problem . 12 1.2. 1 Primary research question . 13 1.2. 2 Secondary research questions . 13 1.3 Research objectives . 14 1.3. 1 Primary research objective . 14 1.3. 2 Secondary research objectives . 15 1.4 Conceptual research framework . 15 1.5 Research design and methodology . 17 1.5. 1 Quantitative research . 17 1.5. 2 Qualitative research . 17 1.5. 3 Data collection . 18 1.5. 4 Data analysis . 19 1.6 Case study research propositions . 19 1.7 Preliminary literature review . 21 1.7. 1 Demand planning . 21 1.7. 2 Technological feasibility . 22 1.7. 3 Skills development . 22 1.7. 4 Financial viability . 23 1.7. 5 Technological advancement . 24 1.8 Outline of the study . 25 1.9 Conclusion . 26 6 Chapter 2: Literature review . 27 2.
Properties of the Sample Mean in Graph Spaces and the Majorize-Minimize-Mean Algorithm

One of the most fundamental concepts in statistics is the concept of sample mean. Properties of the sample mean that are well-defined in Euclidean spaces become unwieldy or even unclear in graph spaces. Open problems related to the sample mean of graphs include: non-existence, non-uniqueness, statistical inconsistency, lack of convergence results of mean algorithms, non-existence of midpoints, and disparity to midpoints. We present conditions to resolve all six problems and propose a Majorize-Minimize-Mean (MMM) Algorithm. Experiments on graph datasets representing images and molecules show that the MMM-Algorithm best approximates a sample mean of graphs compared to six other mean algorithms.
Point and go: Exploring 3D virtual environments

This paper presents our solution to solve the challenge presented at the 3DUI 2012 Contest. The challenge consisted of assisted collaborative navigation in a 3D environment. One user (called power user) has a global view of the 3D environment; alternatively, the other user (called explorer) has a first person view of the environment. The power user uses co-located gestures to manipulate and explore the VR Environment in a power wall like display. These gestures allow the power user to rotate, translate, zoom and place cues for the explorer within the environment, effectively aiding him. The explorer navigates the scene by means of a point and go metaphor: he points to where he wants to go using an optically tracked Wiimote controller; a virtual line connecting the Wiimote in his hand and the target surface is rendered in the VR Environment. We have chosen to use point light sources as cues to the explorer. These point lights show the explorer which direction he should follow to complete the scavenger hunt through the VR Environment. We performed an informal user study showed that users enjoyed completing the given task, despite the initial learning curve for the power user role.
New Approaches for Secure Outsourcing Algorithm for Modular Exponentiations

Outsourcing paradigm is one of the most attractive benefits of cloud computing, where computation workloads can be outsourced to cloud servers by the resourceconstrained devices, such as RFID tags. With this paradigm, cloud users can avoid setting up their own infrastructures. As a result, some new challenges, such as security and checkability, are inevitably introduced. In this paper, we address the problem of secure outsourcing algorithm for modular exponentiations in the one-malicious version of two untrusted program model. We show that our proposed algorithm is more efficient than the state-of-the-art algorithms. On the other hand, we point out in this paper that the first outsource-secure algorithm for simultaneous modular exponentiations proposed recently is insecure, where the sensitive information can be leaked to the malicious servers. As a result, we propose a new and more efficient algorithm for simultaneous modular exponentiations. We also propose the constructions for outsource-secure Cramer-Shoup encryptions and Schnorr signatures which are also more efficient than the state-of-the-art algorithms.
An efficient method for the unsupervised discovery of signalling motifs in large audio streams

Providing effective tools to navigate and access through long audio archives, or monitor and classify broadcast streams, proves to be an extremely challenging task. Main issues originate from the varied nature of patterns of interest in a composite audio environment, the massive size of such databases, and the capability of performing when prior knowledge on audio content is scarce or absent. This paper proposes a computational architecture aimed at discovering occurrences of repeating patterns in audio streams by means of unsupervised learning. The targeted repetitions (or motifs) are called signalling, by analogy with a biological nomenclature, as referring to a broad class of audio patterns (as jingles, songs, advertisements, etc…) frequently occurring in broadcast audio. We adapt a system originally developed for word discovery applications, and demonstrate its effectiveness in a song discovery scenario. The adaption consists in speeding up critical parts of the computations, mostly based on audio feature coarsening, to deal with the large occurrence period of repeating songs in radio streams.
Efficient Codes for Adversarial Wiretap Channels

In [13] we proposed a ({\rho}_r , {\rho}_w )-adversarial wiretap channel model (AWTP) in which the adversary can adaptively choose to see a fraction {\rho}_r of the codeword sent over the channel, and modify a fraction {\rho}_w of the codeword by adding arbitrary noise values to them. In this paper we give the first efficient construction of a capacity achieving code family that provides perfect secrecy for this channel.
A Conceptual Structure for Computer Vision

The research presented in this paper represents several novel conceptual contributions to the computer vision literature. In this position paper, our goal is to define the scope of computer vision analysis and discuss a new categorisation of the computer vision problem. We first provide a novel decomposition of computer vision into base components which we term the axioms of vision. These are used to define researcher-level and developer-level access to vision algorithms, in a way which does not require expert knowledge of computer vision. We discuss a new line of thought for computer vision by basing analyses on descriptions of the problem instead of in terms of algorithms. From this an abstraction can be developed to provide a layer above algorithmic details. This is extended to the idea of a formal description language which may be automatically interpreted thus allowing those not familiar with computer vision techniques to utilise sophisticated methods.
Getting Back on Two Feet: Reliable Standing-up Routines for a Humanoid Robot

To make bipedal locomotion robust, it is not sufficient to rely on postural responses that try to prevent falls, but it is also necessary to detect falls and to implement appropriate recovery procedures. This paper describes general methods for a humanoid robot to stand up from the prone and supine posture. We illustrate the use of these getting-up routines on the example of our robot Jupp. The proposed methods require only a limited number of degrees of freedom and observe common joint-angle limitations. We employed a physics-based robot simulation to analyze the kinematics and dynamics of getting up. The standing-up routines have been implemented on the real robot as well. Tests in our lab and at RoboCup 2005 showed that reliable standing-up is possible after a fall and that such recovery procedures greatly improve the overall robustness of bipedal locomotion.
Toward Scalable Benchmarks for Mass Storage Systems

While mass storage systems have been used for several decades to store large quantities of scientific data, there has been little work on devising standard ways of measuring them. Each system is hand-tuned using parameters that seem to work best, but it is difficult to gauge the potential effect of similar changes on other systems. The proliferation of storage management software and policies has made it difficult for users to make the best choices for their own systems. The introduction of benchmarks will make it possible to gather standard performance measurements across disparate systems, allowing users to make intelligent choices of hardware, software, and algorithms for their mass storage system. This paper presents guidelines for the design of a mass storage system benchmark suite, along with preliminary suggestions for programs to be included. The benchmarks will measure both peak and sustained performance of the system as well as predicting both short-term and long-term behavior. These benchmarks should be both portable and scalable so they may be used on storage systems from tens of gigabytes to petabytes or more. By developing a standard set of benchmarks that reflect real user workload, we hope to encourage system designers and users to publish performance figures that can be compared with those of other systems. This will allow users to choose the system that best meets their needs best and give designers a tool with which they can measure the performance effects of improvements to their systems.
The Hedonic Experience of Enjoyment and Its Relationship to Informal Learning: A Study of Museum Websites

Online hedonic experiences are increasingly of interest in both research and practice. In particular, it has been proposed that ‘traditional usability approaches are too limited and must be extended to encompass enjoyment’ (Blythe and Wright 2003, p.xvi). The aim of this study was to investigate the relationships among: (i) website design features; (ii) user’s experience of enjoyment; and (iii) informal learning such as that occurring with a museum website. A cross-over experimental design was employed with web pages from the National Palace Museum, Taiwan. Results indicated that, as expected, a multimedia game-based ‘lesson’ led to both more enjoyment and more learning than a text-based ‘lesson’. With text-based pages more enjoyment also meant more learning. The situation was complicated, however, with the game-based pages, as results were not in the expected direction. The study points to the need for more research in this complex area.
E. coli secreted protein F promotes EPEC invasion of intestinal epithelial cells via an SNX9‐dependent mechanism

Enteropathogenic Escherichia coli (EPEC) infection requires the injection of effector proteins into intestinal epithelial cells (IECs) via type 3 secretion. Type 3‐secreted effectors can interfere with IEC signalling pathways via specific protein–protein interactions. For example, E. coli secreted protein F (EspF) binds sorting nexin 9 (SNX9), an endocytic regulator, resulting in tubulation of the plasma membrane. Our aim was to determine the mechanism of EspF/SNX9‐induced membrane tubulation. Point mutation of the SNX9 lipid binding domains or truncation of the EspF SNX9 binding domains significantly inhibited tubulation, as did inhibition of clathrin coated pit (CCP) assembly. Although characterized as non‐invasive, EPEC are known to invade IECs in vitro and in vivo. Indeed, we found significant invasion of Caco‐2 cells by EPEC, which, like tubulation, was blocked by pharmacological inhibition of CCPs. Interestingly, however, inhibition of dynamin activity did not prevent tubulation or EPEC invasion, which is in contrast to Salmonella invasion, which requires dynamin activity. Our data also indicate that EPEC invasion is dependent on EspF and its interaction with SNX9. Together, these findings suggest that EspF promotes EPEC invasion of IECs by harnessing the membrane‐deforming activity of SNX9.
HMM2- extraction of formant structures and their use for robust ASR

As recently introduced in [1], an HMM2 can be considered as a particular case of an HMM mixture in which the HMM emission probabilities (usually estimated through Gaussian mixtures or an artiﬁcial neural network) are modeled by state-dependent, feature-based HMM (referred to as frequency HMM). A general EM training algorithm for such a structure has been developed [2]. Although there are numerous motivations for using such a structure, and many possible ways to exploit it, this paper will mainly focus on one particular instantiation of HMM2 in which the frequency HMM will be used to extract formant structure information, which will then be used as additional acoustic features in a standard Automatic Speech Recognition (ASR) system. While the fact that this architecture is able to automatically extract meaningful formant information is interesting by itself, empirical results also show the robustness of these features to noise, and their potential to enhance state-of-the-art noise-robust HMM-based ASR.
Register level sort algorithm on multi-core SIMD processors

State-of-the-art hardware increasingly utilizes SIMD parallelism, where multiple processing elements execute the same instruction on multiple data points simultaneously. However, irregular and data intensive algorithms are not well suited for such architectures. Due to their importance, it is crucial to obtain efficient implementations. One example of such a task is sort, a fundamental problem in computer science. In this paper we analyze distinct memory accessing models and propose two methods to employ highly efficient bitonic merge sort using SIMD instructions as register level sort. We achieve nearly 270x speedup (525M integers/s) on a 4M integer set using Xeon Phi coprocessor, where SIMD level parallelism accelerates the algorithm over 3 times. Our method can be applied to any device supporting similar SIMD instructions.
Settlement Modelling of Raft Footing Founded on Oferekpe/Abakaliki Shale in South East Region of Nigeria

In engineering practice, settlement of foundations are experimentally determined or numerically modelled based on conventional saturated soil mechanics principles. The study area, Oferekpe in Abakaliki LGA of Ebonyi State, South Eastern Region of Nigeria is characterised with sedimentary formations highly susceptible to compression under applied load. The study was aimed at evaluating raft footing settlement by both analytical and numerical modelling methods and determine the effect of raft thickness on settlement. Standard penetration test (SPT) data was used to correlate soil properties that were used together with laboratory results to obtain the input parameters used for the prediction of settlement. Four footing embedment depths of 1.5, 3.0, 4.5 and 6.0 m with applied foundation pressures of 50, 100, 200, 300, 400 and 500kN/m2 were considered using a raft footing dimension of 20 x 20 m2 at varying thickness of 0.5, 0.75 and 1.0 m. The numerical modelling finite element application package used was Plaxis 3D. For applied pressure of 100 kN/m2 and at footing embedment depths of 1.5, 3.0, 4.5 and 6.0 m, settlement values of (21.89, 11.51, 9.04 and 6.52), (19.70, 8.60, 6.41 and 4.39), (25.62, 14.88, 12.05 and 9.27) and (25.20, 11.59, 5.57 and 2.58) were respectively predicted by the elastic, semi-empirical, empirical and finite element methods. The elastic method of predicting foundation settlement proposed by Steinbrenner yielded a very close range results generally to those predicted by finite element method. It was generally observed that thickness of raft footing has no significant effect on the predicted settlement.
Backstitch: Counteracting Finite-Sample Bias via Negative Steps

In this paper we describe a modification to Stochastic Gradient Descent (SGD) that improves generalization to unseen data. It consists of doing two steps for each minibatch: a backward step with a small negative learning rate, followed by a forward step with a larger learning rate. The idea was initially inspired by ideas from adversarial training, but we show that it can be viewed as a crude way of canceling out certain systematic biases that come from training on finite data sets. The method gives∼ 10% relative improvement over our best acoustic models based on lattice-free MMI, across multiple datasets with 100-300 hours of data.
Monitoring the Activation of the DNA Damage Response Pathway in a 3D Spheroid Model

Monitoring the DNA-Damage Response (DDR) activated pathway in multicellular tumor spheroid models is an important challenge as these 3D models have demonstrated their major relevance in pharmacological evaluation. Herein we present DDR-Act-FP, a fluorescent biosensor that allows detection of DDR activation through monitoring of the p21 promoter p53-dependent activation. We show that cells expressing the DDR-Act-FP biosensor efficiently report activation of the DDR pathway after DNA damage and its pharmacological manipulation using ATM kinase inhibitors. We also report the successful use of this assay to screen a small compound library in order to identify activators of the DDR response. Finally, using multicellular spheroids expressing the DDR-Act-FP we demonstrate that DDR activation and its pharmacological manipulation with inhibitory and activatory compounds can be efficiently monitored in live 3D spheroid model. This study paves the way for the development of innovative screening and preclinical evaluation assays.
Motion Control of a Robotic Puppet through a Hybrid Motion Capture Device

In this paper we explore the motion control of a robotic puppet through motion capture data. A motion mapping technique is investigated to map the human motion into marionette motion, and from that calculate the rotation of the servo motors to achieve desired marionette motions. A software was developed to capture human motions utilizing a bend-twist sensor system, and use the motion data to control the robotic marionette by either offline control method or online control method (real-time). We also propose the idea of integrating human into the system to close the control loop. Experimental results show that our motion mapping enables puppet to follow the actor motions with good correspondence.
Understanding a large corpus of web tables through matching with knowledge bases: an empirical study

Extracting and analyzing the vast amount of structured tabular data available on the Web is a challenging task and has received a significant attention in the past few years. In this paper, we present the results of our analysis of the contents of a large corpus of over 90 million Web Tables through matching table contents with instances from a public cross-domain ontology such as DBpedia. The goal of this study is twofold. First, we examine how a large-scale matching of all table contents with a knowledge base can help us gain a better understanding of the corpus beyond what we gain from simple statistical measures such as distribution of table sizes and values. Second, we show how the results of our analysis are affected by the choice of the ontology and knowledge base. The ontologies studied include DBpedia Ontology, Schema.org, YAGO, Wikidata, and Freebase. Our results can provide a guideline for practitioners relying on these knowledge bases for data analysis.
The Development of the Mealings, Demuth, Dillon, and Buchholz Classroom Speech Perception Test.

PURPOSE Open-plan classroom styles are increasingly being adopted in Australia despite evidence that their high intrusive noise levels adversely affect learning. The aim of this study was to develop a new Australian speech perception task (the Mealings, Demuth, Dillon, and Buchholz Classroom Speech Perception Test) and use it in an open-plan classroom to assess how intrusive noise affects speech perception. METHOD The first part of this article describes how the online 4-picture choice speech perception task materials were created. The second part focuses on the study involving twenty-two 5- to 6-year-old children in an open-plan classroom who completed the task while other classes engaged in quiet and noisy activities. RESULTS Children's performance accuracy, number of responses, and speed were lower in the noisy condition compared with the quiet condition. In addition, children's speech perception scores decreased the farther away they were seated from the loudspeaker. Overall, the children understood and were engaged in the task, demonstrating that it is an appropriate tool for assessing speech perception live in the classroom with 5- to 6-year-old children. CONCLUSIONS The results suggest that the Mealings, Demuth, Dillon, and Buchholz Classroom Speech Perception Test is a helpful tool for assessing speech perception in classrooms and that it would be beneficial to use in future research investigating how classroom design and noise affect speech perception.
Inhibition of Notch signalling ameliorates experimental inflammatory arthritis

Objective To test the hypothesis that Notch signalling plays a role in the pathogenesis of rheumatoid arthritis (RA) and to determine whether pharmacological inhibition of Notch signalling with γ-secretase inhibitors can ameliorate the RA disease process in an animal model. Methods Collagen-induced arthritis was induced in C57BL/6 or Notch antisense transgenic mice by immunisation with chicken type II collagen (CII). C57BL/6 mice were administered with different doses of inhibitors of γ-secretase, an enzyme required for Notch activation, at disease onset or after onset of symptoms. Severity of arthritis was monitored by clinical and histological scores, and in vivo non-invasive near-infrared fluorescence (NIRF) images. Micro-CT was used to confirm joint destruction. The levels of CII antibodies and cytokines in serum were determined by ELISA and bead-based cytokine assay. The expression levels of cytokines were studied by quantitative PCR in rheumatoid synovial fibroblasts. Results The data show that Notch signalling stimulates synoviocytes and accelerates their production of proinflammatory cytokines and immune responses involving the upregulation of IgG1 and IgG2a. Pharmacological inhibition of γ-secretase and antisense-mediated knockdown of Notch attenuates the severity of inflammatory arthritis, including arthritis indices, paw thickness, tissue damage and neutrophil infiltration, and reduces the levels of active NF-κB, ICAM-1, proinflammatory cytokines and matrix metalloproteinase-3 activity in the mouse model of RA. Conclusions These results suggest that Notch is involved in the pathogenesis of RA and that inhibition of Notch signalling is a novel approach for treating RA.
A Comparative Performance Analysis of PID Tuning Techniques Based on Frequency Response Specification

This paper presents an overview of ProportionalIntegral-Derivative (PID) controller and it's Tuning. Two systems are selected for study. One is higher order system and the other is first order system with time delay. The performance of PID tuning techniques is analyzed on the basis of frequency response parameter that is Phase Margin. Simulation results are presented and performances of different PID tuning techniques are compared.