Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimation of illumination distribution using a specular sphere

A method has been proposed for acquiring an omnidirectional image of a scene using a specular sphere (namely a mirror ball). The method takes the reflected image on the specular sphere located at a desired position in a scene by an ordinary camera. This paper discusses the relation between the reflected image of the scene and the radiance of the scene. Due to the reflection on the sphere, the final image on the camera has geometric distortion. There are imaging systems covering a wide angle by the lens system itself, e.g., a fish-eye lens. The image obtained by such lens systems has similar geometrical distortion. However, the effect of the distortion on the image brightness is different. We point out that the image distortion due to the lens system affects the image brightness, while that due to the reflection on the specular sphere does not. Most of the discussion can be applied to the methods using a curved mirror to obtain a wide angle image.
An Exploratory Study On the Effects of Electronic Collaboration In An MBA Core Course in Information Systems

Internet based collaboration tools are increasingly being used in information systems courses. This study reports on the results of one such implementation at Lawrence Technological University. Using a sample of 51 students, the researcher explores three hypotheses. First, students in a class with electronic collaboration will work on course material more days during the week than those without. Second, students will perceive that quiet peers can more freely express themselves. Third, students in a course with electronic collaboration will perceive a greater gain in their Internet skills compared to those in a course without collaboration. The researcher supported his second hypothesis.
Clientelism in the Public Sector: Why Public Service Reforms Fail and What to Do About it

In many developing countries (and beyond), public sector workers are not just simply implementers of policies designed by the politicians in charge of supervising them -- so called agents and principals, respectively. Public sector workers can have the power to influence whether politicians are elected, thereby influencing whether policies to improve service delivery are adopted and how they are implemented, if at all. This has implications for the quality of public services: if the main purpose of the relationship between politicians and public servants is not to deliver quality public services, but rather to share rents accruing from public office, then service delivery outcomes are likely to be poor. This paper reviews the consequences of such clientelism for improving service delivery, and examines efforts to break from this"bad"equilibrium, at the local and national levels.
IADIS INTERNATIONAL CONFERENCE on COGNITION AND EXPLORATORY LEARNING IN DIGITAL AGE ( CELDA 2009 )

This work describes an eye tracking study of the e-learning system Moodle outlining how Moodle’s learning materials are explored, selected and processed. The goal of this study was to investigate several cognitive variables and the exploratory learning processes itself. The experiment addressed research objectives such as the individual order of selecting learning material, the visual scanning of Moodle's environment, the importance of "Gestalt laws" respectively rules of pre-attentive perception, the influence of the involvement-factor as well as usability aspects. Discussion and analysis of the collected survey data indicate some interesting results. The investigation indentified that first fixations of a Moodle page basically reveal a sort of ‘inventory’ of informative elements and that visual perceptionrules highly structure participant’s exploration. Moreover involvement measurements implied that learners with ‘high’ involvement tend to process teaching material uniformly, whereas participants of the category ‘low’ adopt noticeably irregular fixation-densities, due to intentional skipping of content or monotone reading.
CONTROL OF LABORATORY MODEL OF PENDUBOT

Abstract: This paper presents the concept of swing up and balancing control of a pendubot laboratory model. The pendubot is a two-link under actuated robotic mechanism, presenting the classic inverted pendulum problem; well suited for control theory education as well as for research in the control of nonlinear mechatronic systems with fast dynamics. Brief introduction into the laboratory hardware and its mathematical modeling is followed by an account on the controller design process. The proposed control scheme is verified in experiment and results are evaluated in the presented work. The swing up of the pendulum is based on a method of impulse build up of energy. A fourth order linearized time-invariant state-space system model is identified for the pendubot system. The basic balancing control is then based on a linear-quadratic (LQ) controller, implemented and tested real-time on the experimental setup. Laboratory verification confirms, that the linear quadratic controller actuated system response is excellent, however the inclusion of process constraints in a model predictive control (MPC) based balancing scheme could potentially offer numerous benefits.
Modelling methods for web application verification and testing: state of the art

Models are considered an essential step in capturing different system behaviours and simplifying the analysis required to check or improve the quality of software. Verification and testing of web software requires effective modelling techniques that address the specific challenges of web applications. In this study we survey 24 different modelling methods used in web site verification and testing. Based on a short catalogue of desirable properties of web applications that require analysis, two different views of the methods are presented: a general categorization by modelling level, and a detailed comparison based on property coverage. Copyright © 2008 John Wiley & Sons, Ltd.
2 LabVIEW based Cyber Physical System Emulators

Technical Articles • Karthikrajan Senthilnathan, K. Iyswarya Annapoorani, “Cyber Physical Emulators for Power System and Power Electronics Studies”. • Md. Ariful Islam, “Simplex Architectures for Cyber-Physical Systems”. • Ziyu Pan, Long Chen, Wulin Huang, “A Targetless Method For Automated Calibration Of Lidar-Camera System”. • Chao Huang, “Model-based Control and Verification of Autonomous Vehicle Systems”. • Umit Demirbaga, Devki Nandan Jha, Nick Booth, Tony Roberts, Tejal Shah, Rajiv Ranjan, “A Batch and Real-time Data Analytics Framework for Healthcare Applications”. • Yawen Wu, Zhenge Jia, Jingtong Hu, “Energy Harvesting Powered Embedded Systems”.
Reconciling Point-based and Interval-based Semantics in Temporal Relational Databases : A Proper Treatment of the Telic / Atelic Distinction

Any software made available via TIMECENTER is provided " as is " and without any express or implied warranties, including, without limitation, the implied warranty of merchantability and fitness for a particular purpose. The TIMECENTER icon on the cover combines two " arrows. " These " arrows " are letters in the so-called Rune alphabet used one millennium ago by the Vikings, as well as by their precedessors and successors. The Rune alphabet (second phase) has 16 letters, all of which have angular shapes and lack horizontal lines because the primary storage medium was wood. Runes may also be found on jewelry, tools, and weapons and were perceived by many as having magic, hidden powers. The two Rune arrows in the icon denote " T " and " C, " respectively. Abstract The analysis of the semantics of temporal data and queries plays a central role in the area of temporal databases. Although many different algebrae and models have been proposed, almost all of them are based on a point-based (snapshot) semantics for data. On the other hand, in the areas of linguistics, philosophy, and, recently, artificial intelligence, a debated issue concerns the use of an interval-based versus a point-based semantics. In this paper, we first show some problems inherent in the adoption of a point-based semantics for data, and argue that these problems arise because there is no distinction drawn in the data between telic and atelic facts. We then introduce a three-sorted temporal model and algebra which properly copes with these issues, and which achieves a great flexibility via the introduction of coercion functions for transforming relations of one sort into relations of the other at query time. We
Local Crowdsourcing for Audio Annotation : the Elevator Annotator Platform

Crowdsourcing is useful in collecting large numbers of annotations for various datasets. Local crowdsourcing is a variant where annotations are done at specific physical locations. This paper describes a local crowdsourcing concept, platform and experiment to gather annotations for an audio archive. For the experiment, we developed a hardware platform and its supporting software functionality, designed to be deployed in building elevators. To evaluate the effectiveness of the platform , test the impact of location, and the interaction interface on the annotation results, we set up an experiment in two locations. In each location we used two different user interaction modalities. Our results show that our simple local crowdsourcing setup achieves significant accuracy levels and generates up to 4 annotations per hour, depicting as well the correlation between location and accuracy.
ML2R Coding Nuggets: Linear Programming

We revisit the problem of numerically solving the Schrödinger equation for a one-dimensional quantum harmonic oscillator. We reconsider our previous finite difference scheme and discuss how higher order finite differences can lead to more accurate solutions. In particular, we will consider a five point stencil to approximate second order derivatives and implement the approach using SciPy functions for sparse matrices.
Stroke Effects of Feedback-Based Visual Line-Orientation Discrimination Training for Visuospatial Disorders

Background. Patients with right or more rarely left parietotemporal lesions after stroke may have profound visuospatial disorders that impair activities of daily living (ADL) and long-term outcome. Clinical studies indicate improvements with systematic training of perception. Studies of perceptual learning in healthy persons suggest rapid improvements in perceptual learning of spatial line orientation with partial transfer to nontrained line orientations. Objective. The authors investigated a novel feedback-based perceptual training procedure for the rehabilitation of patients after stroke. Methods. In an uncontrolled trial, 13 participants showing profound deficits in line orientation and related visuospatial tasks within 12 to 28 weeks of onset performed repetitive feedback-based, computerized training of visual line orientation over4 weeks of treatment. Visual line-orientation discrimination and visuospatial and visuoconstructive tasks were assessed before and after training. Results. The authors found (a) rapid improvements in trained but also in nontrained spatial orientation tests in all 13 participants, partially up to a normal level; (b) stability of the obtained improvements at 2-month follow-up; (c) interocular transfer of training effects to the nontrained eye in 2 participants suggesting a central, postchiasmatic locus for this perceptual improvement; and (d) graded transfer of improvements to related spatial tasks, such as horizontal writing, analog clock reading, and visuoconstructive capacities but no transfer to unrelated measures of visual performance. Conclusions. These results suggest the potential for treatment-induced improvements in visuospatial deficits by feedbackbased, perceptual orientation training as a component of rehabilitation after stroke.
Eecient Reinforcement Learning through Symbiotic Evolution Editor: Leslie Pack Kaelbling

This article presents a new reinforcement learning method called SANE (Symbiotic, Adaptive Neuro-Evolution), which evolves a population of neurons through genetic algorithms to form a neural network capable of performing a task. Symbiotic evolution promotes both cooperation and specialization, which results in a fast, eecient genetic search and discourages convergence to suboptimal solutions. In the inverted pendulum problem, SANE formed eeective networks 9 to 16 times faster than the Adaptive Heuristic Critic and 2 times faster than Q-learning and the GENITOR neuro-evolutionapproachwithout loss of generalization. Such eecient learning, combined with few domain assumptions, make SANE a promising approach to a broad range of reinforcement learning problems, including many real-world applications.
TAK 1 is indispensable for development of T cells and prevention of colitis by the generation of regulatory T cells

Transforming growth factor (TGF)-b-activating kinase 1 (TAK1) is critical for Toll-like receptorand tumor necrosis factor-mediated cellular responses. In B cells, TAK1 is essential for the activation of mitogen-activated protein kinases (MAPKs), but not nuclear factor-jB (NF-jB), in antigen receptor signaling. In this study, we generate T cell-specific TAK1-deficient (LckTak1) mice and show that TAK1 is indispensable for the maintenance of peripheral CD4 and CD8 T cells. In thymocytes, TAK1 is essential for TCR-mediated activation of both NF-jB and MAPKs. Additionally, LckTak1 mice developed colitis as they aged. In these mice, accumulations of activated/ memory T cells as well as B cells were observed. Development of regulatory T (Treg) cells in thymus was abrogated in LckTak1 mice, suggesting that the loss of Treg cells is the cause of the disease. Together, the results show that TAK1, by controlling the generation of central Treg cells, is important for preventing spontaneously developing colitis.
HateCircle and Unsupervised Hate Speech Detection incorporating Emotion and Contextual Semantic

copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. © 2022 Association for Computing Machinery. 0360-0300/2022/1-ART1 $15.00 https://doi.org/10.1145/3576913 ACM Trans. Asian Low-Resour. Lang. Inf. Process. HateCircle and Unsupervised Hate Speech Detection incorporating Emotion and Contextual Semantic SAYANI GHOSAL
Screening E ¢ ciency of Networks

In this paper, we study screening e¢ ciency of networks as organizations in comparison with polyarchies and hierarchies. Firstly, we briey characterize these organizational architectures, then we rank them in the case of in nitely many and nitely many decisional units. As we show and discuss, networks are more e¢ cient than polyarchies and hierarchical architectures with good initial choice portfolios. In opposition, whether Type II errors are very likely to occur, a hierarchy preforms better than polyarchies and networks. Finally, we illustrate how these organizations perform when a budget constraint has to be ful lled. 1To contact the author: Department of Economics, 2 Piazza Scaravilli, 40126, Bologna, Italy. Tel:++390512098662; Fax: ++390512098040; e-mail: lanzi00@economia.unibo. it
The future of virtual racing

We created a dataset of episodes from our daily soap opera GTST with shot-level annotations of recurring video content. Each GTST episode starts with about a minute of recaps from previous episodes and ends with a short preview of the next episode. This recurring content makes for ideal training material in a weakly-supervised learning task for what content is interesting to include in promotional material.
Gamal Fahmy

: Sub-band coding has long been utilized and adopted in different compression, coding and reconstruction techniques in most signal processing applications. It has wide applications in communications, bit rate codec’s, sampling, and compression for images, videos and speech. However sub-band coding systems in general suffer from a certain amount of shift variance of the output reconstructed signal, due to the frequency overlap between different sub-bands in the analysis stage. This overlap is known as non-ideal anti-aliasing. In this paper we simplify the shift variance analysis of sub-band coding systems in general, and we present different metrics that have been reported in the literature to measure the bounds of shift variance for Perfect Reconstruction (PR) sub-band systems, we simplify its mathematical analysis and illustrate with graphs the reasons for these bounds and compare them. We apply these metrics on Biorthogonal, Orthogonal and Bspline wavelets and present the worst case scenario for different input signals in terms of shift variance for all these sub-band coding systems, both numerically and graphically. We finally compare the shift variance behavior for different sub-band PR systems for different types of input signals.
Recent Advances in Nutritional Sciences Use of Exfoliated Cells from Target Tissues to Predict Responses to Bioactive Food Components 1

A host of bioactive food components have been proposed to promote health and reduce the risk of disease states. It is clear that not all individuals respond identically to these essential and nonessential food components. Genetic polymorphisms may influence absorption, metabolism and accumulation of bioactive food components, thereby influencing their actions in target tissues. Unfortunately, serum concentrations of bioactive food components may not correlate with tissue concentrations and may therefore underor overestimate the response in target tissues. Exfoliated cells may be useful to assess the actions of nutrients in specific tissues. Although not extensively examined, evidence already suggests the usefulness of these cells in predicting changes in gene expression, DNA methylation, DNA damage, protein expression and accumulation of dietary components. Although there are limitations on the collection of exfoliated cells, the inaccessibility of tissues they can represent raises intriguing possibilities for their ability to predict the outcome of nutritional intervention studies. J. Nutr. 133: 1769–1772, 2003.
CLEF : Limiting the Damage Caused by Large Flows in the Internet Core ( Technical Report )

The detection of network flows that send excessive amounts of traffic is of increasing importance to enforce QoS and to counter DDoS attacks. Large-flow detection has been previously explored, but the proposed approaches can be used on high-capacity core routers only at the cost of significantly reduced accuracy, due to their otherwise too high memory and processing overhead. We propose CLEF, a new large-flow detection scheme with low memory requirements, which maintains high accuracy under the strict conditions of high-capacity core routers. We compare our scheme with previous proposals through extensive theoretical analysis, and with an evaluation based on worst-case-scenario attack traffic. We show that CLEF outperforms previously proposed systems in settings with limited memory.
VARIATION DISCOVERY AND EVOLUTIONARY PATTERNS OF PROTEIN DOMAIN FAMILIES IN 15 SPECIES OF BIRDS

1 RESUMEN.2 OBJECTIVES.3 INTRODUCTION.4 Copy number variation.4 Protein domain expansions.4 The use of CORTEX for heterozygous variation detection.6 De Bruijn graphs.6 MATERIALS AND METHODS.8 NGS DATA COLLECTION.8 REFERENCE GENOME COLLECTION.8 QUALITY CONTROL.9 CORTEX ANALYSES.9 • Binary dumping.9 • Bubble calling.10 • Obtaining vcf files.11 • Selecting and filtering vcf files.14 THE NUMBER OF VARIANTS.14 HETEROZYGOUS VARIATION IN RELATION TO POPULATION SIZE.14 ANALYSIS OF THE PROTEIN DOMAINS.15 • Protein domain detection and analysis.15 • Analysing the number of copies of the protein domains.16 • Finding variants for the protein domains in all species.17 RESULTS.23 VARIANT CALLING.23 NUMBER OF VARIANTS AND POPULATION SIZE.24 PROTEIN DOMAIN ANALYSIS.25 SEARCHING FOT SNVs IN PROTEIN DOMAINS.27 DISCUSSION.31 TOTAL SNVs FOUND WITH CORTEX.31 PROTEIN DOMAIN ANALYSES.32 CONCLUSION.34 ANNEX 1.35 ANNEX2.36 BIBLIOGRAPHY.37
Functional Magnetic Resonance Imaging Investigation of Overlapping Lateral Occipitotemporal Activations Using Multi-Voxel Pattern Analysis

Several functional areas are proposed to reside in human lateral occipitotemporal cortex, including the motion-selective human homolog of macaque area MT (hMT), object-form-selective lateral occipital complex (LO), and body-selective extrastriate body area (EBA). Indeed, several functional magnetic resonance imaging (fMRI) studies have reported significant activation overlap among these regions. The standard interpretation of this overlap would be that the common areas of activation reflect engagement of common neural systems. Alternatively, motion, object form, and body form may be processed independently within this general region. To distinguish these possibilities, we first analyzed the lateral occipitotemporal responses to motion, objects, bodies, and body parts with whole-brain group-average analyses and within-subjects functional region of interest (ROI) analyses. The activations elicited by these stimuli, each relative to a matched control, overlapped substantially in the group analysis. When hMT, LO, and EBA were defined functionally within subjects, each ROI in each hemisphere (except right-hemisphere hMT) showed significant selectivity for motion, intact objects, bodies, and body parts, although only the peak voxel of each region was tested. In contrast, multi-voxel analyses of variations in selectivity patterns revealed that visual motion, object form, and the form of the human body elicited three relatively independent patterns of fMRI activity in lateral occipitotemporal cortex. Multi-voxel approaches, in contrast to other methods, can reveal the functional significance of overlapping fMRI activity in extrastriate cortex and, by extension, elsewhere in the brain.
DeepPurpose: a Deep Learning Library for Drug-Target Interaction Prediction and Applications to Repurposing and Screening

Accurate prediction of drug-target interactions (DTI) enables drug discovery tasks, including virtual screening and drug repurposing, which can shorten the time to identify promising drug candidates and provide cures to patients. Recently, there is a growing number of research that developed deep learning (DL) models for DTI. Despite their superior performance, these research models are difficult to use in real drug discovery practice due to the complexity of deploying the research code as well as the restricted data formatting, model capacity, and evaluation setting. We present DeepPurpose, a comprehensive and easy-to-use software toolkit for DL based drug-target interaction (DTI) prediction with applications to drug screening and repurposing. The unique feature of DeepPurpose is that it enables non-computational drug development scientists to identify drug candidates based on five pre-trained DL models with only a few lines of codes. Further, computer scientists can use DeepPurpose to train customized DTI prediction models with 15 drug and target encodings and 50+ novel DL architectures. To tackle method development challenges, DeepPurpose also supports various data split settings and preloads five benchmarking datasets. We demonstrated that DeepPurpose allows users to obtain state-of-the-art prediction performance on several benchmark datasets. We also presented several case studies, including a study on drug repurposing for COVID-19, where promising drug candidates currently investigated in clinical trials are ranked high in DeepPurpose predictions.