Miracle-dz/UniFAR-FTUs huggingface dataset:
UvA-DARE ( Digital Academic Repository ) Network Models to Organize a Dispersed Literature : The Case of Misunderstanding Analysis of Covariance

Derks, K. ; Burger, J.; van Doorn, J.; Kossakowski, J.J.; Matzke, D. ; Atticciati, L. ; Beitner, J.; Benzesin, V. ; de Bruijn, A.L. ; Cohen, T.R.H. ; Cordesius, E.P.A. ; van Dekken, M. ; Delvendahl, N. ; Dobbelaar, S. ; Groenendijk, E.R. ; Hermans, M.E. ; Hiekkaranta, A.P.; Hoekstra, R.H. A. ; Hoffmann, A.M.; Hogenboom, S.A.M.; Kahveci, S. ; Karaban, I.J.; Kevenaar, S. ; te Koppele, J.L. ; Kramer, A-W. ; Kroon, E. ; Kucharský, Š. ; Lieuw-On, R. ; Lunansky, G. ; Matzen, T.P.; Meijer, A. ; Nieper, A. ; de Nooij, L. ; Poelstra, L. ; van der Putten, W.J.; Sarafoglou, A. ; Schaaf, J.V. ; van de Schraaf, S.A. J.; van Schuppen, S. ; Schutte, M.H. M. ; Seibold, M. ; Slagter, S.K. ; Snoek, A.C. ; Stracke, S. ; Tamimy, Z. ; Timmers, B. ; Tran, H. ; Uduwa-Vidanalage, E.S. ; Vergeer, L. ; Vossoughi, L. ; Yücel, D.E. ; Wagenmakers, E. -J.
Precise reconstruction of indoor environments using RGB-depth sensors

I PUBLICATIONS ARISING FROM THE THESIS . III ACKNOWLEDGMENTS . V TABLE OF CONTENTS . VI LIST OF FIGURES . IX LIST OF TABLES . XII LIST OF ABBREVIATION . XIII LIST OF SYMBOLS . XV CHAPTER 1: INTRODUCTION . 1 1.1 MOTIVATION . 1 1.2 THESIS OBJECTIVES . 4 1.3 THESIS CONTRIBUTIONS AND OUTLINES . 6 CHAPTER 2: RECENT DEVELOPMENT ON 3D MODELING USING RGBD SENSORS . 8 2.
Effective Energy Detection for IoT Systems Against Noise Uncertainty at Low SNR

This paper deals with spectrum sensing for cognitive radio-based Internet of Things (IoT) systems and their coexistence with Long Term Evolution (LTE) systems. Due to the sparsity of the covariance matrix of IoT/LTE signals, we reveal that the likelihood ratio test approximates to energy detection (ED) at low signal to noise ratio. However, the noise (power) uncertainty can degrade the performance of ED severely, especially when low-cost IoT devices are employed for spectrum sensing. To tackle this issue, we derive the relationship among noise power, total power, and autocorrelation coefficient of received signals, and propose an unbiased estimator of noise power without the knowledge of the presence/absence of IoT/LTE signals. We then design a new ED with multiple estimates of noise power from historical and current sensing data, and analyze its theoretical performance. Numerical results are provided to verify the theoretical results and demonstrate the superior performance of the proposed detector. It is shown that, by exploiting sufficient historical sensing data, the performance of the proposed ED can closely approach that of the ideal ED.
Self-Organizing Neural Network for Optimum Supervised Learning

This work introduces a new algorithm called the Self-Organizing Neural Network (SONN), and demonstrates its use in a system identification task. The algorithm constructs a network, chooses the neuron functions, and adjusts the weights. Here, it is compared to the Back-Propagation algorithm in the identification of the chaotic time series. The results show that SONN constructs a simpler, more accurate model, requiring less training data and epochs. The algorithm can also be applied as a classifier. 1.1 THE SYSTEM IDENTIFICATION PROBLEM In various engineering applications, it is important to be able to estimate, interpolate, and extrapolate the behavior of an unknown system when only its
Fluoro-5-Fluoro-1--D-Arabinofuranosyluracil as a Potential PET Imaging Agent for Suicide Gene Expression

2-Deoxy-2-18F-fluoro-5-fluoro-1--D-arabinofuranosyluracil ( 18 F-FFAU) has been synthesized and evaluated in HT-29 cells as a potential PET agent for herpes simplex virus type 1 thymidine kinase (HSV1-tk) gene expression. Methods: 2-Deoxy-2- 18 Ffluoro-1,3,5-tri-O-benzoyl--D-arabinofuranose was prepared by the reaction of the respective 2-triflate with tetrabutylammonium 18F-fluoride. The fluorosugar was converted to its 1-bromo derivative and coupled with protected 5-fluorouracil. The crude product was hydrolyzed in base and purified by high-performance liquid chromatography to obtain the 18 F-FFAU. In vitro studies were performed in HT-29 cells by incubation at various time points. In vivo studies including biodistribution and microPET were performed in tumor-bearing nude mice. Results: The radiochemical yield was 20%‐30% decay corrected with an average of 25% in 4 runs. Radiochemical purity was 99% and average specific activity was 85 GBq/mol (2,300 mCi/mol) (end of synthesis). In vitro accumulation of 3H-FFAU in HSV1-tk‐expressing cells was 180-fold (P 0.001) higher than that in the wild-type cells between 30 and 120 min. In vivo uptake of 3H-FFAU in HSV1-tk‐ positive tumors a t2hw as8-fold (P 0.001) higher than that in the control tumors. Tumor uptake (percentage injected dose per gram of tissue) and the uptake ratio (tk-positive to wild type) of 3H-FFAU in tk-positive cells was higher compared with those of our earlier studies using 2- 14 C-deoxy-2-fluoro-5-methyl-1--Darabinofuranosyluracil (14C-FMAU) and 9-(4-18F-fluoro-3-hydroxymethylbutyl)guanine ( 18 F-FHBG) in the same cell lines. microPET on tumor-bearing nude mice also demonstrated a very high uptake of 18 F-FFAU in tk-positive tumors compared with that of the control tumor without significant accumulation in other organs. Conclusion: These results demonstrate that 18 F-FFAU has supe
Within-herd phenotypic, genetic and environmental trend lines for beef cattle breeders.

: Computational procedures were developed to compute within-herd phenotypic, genetic and environmental trend lines on a breed-wide basis by using best linear unbiased estimates of fixed effects and predictors of random sire and dam genetic effects. Procedures were demonstrated by using weaning weight performance records from 20 herds participating in the American Angus Herd Improvement Program. Current evaluation procedures used by several beef breed associations make it possible to provide such information to breeders on a routine basis, along with within-herd breeding values. The within-herd genetic trends are relative to the national genetic evaluation base. Procedures are summarized in addition to presentation of within-herd trend lines for four of the 20 herds, demonstrating the utility of such information to breeders, along with a discussion of several alternative presentation formats.
Expanding the Limits of Vision-Based Autonomous Path Following

Expanding the Limits of Vision-Based Autonomous Path Following Michael Paton Doctor of Philosophy Graduate Department of Aerospace Engineering University of Toronto 2017 Autonomous path-following systems allow robots to traverse large-scale networks of paths using on-board sensors. These methods are well suited for applications that involve repeated traversals of constrained paths such as factory floors, orchards, and mines. Through the use of inexpensive, commercial, vision sensors, these algorithms have the potential to enable robotic applications across multiple industries. However, these applications will demand algorithms capable of long-term autonomy. This poses a difficult challenge for vision-based systems in unstructured and outdoor environments, whose appearances are highly variable. While techniques have been developed to perform localization across extreme appearance change, most are not suitable or untested for vision-in-the-loop systems such as autonomous path following, which requires continuous metric localization to keep the robot driving. This thesis extends the performance of vision-based autonomous path following through the development of novel localization and mapping techniques. First, we present the following generic localization frameworks: i) a many-to-one localization framework that combines data associations from independent sources of information into single state-estimation problems, and ii) a multi-experience localization and mapping system that provides metric localization to the manually taught path across extreme appearance change using bridging experiences gathered during autonomous operation. We use these frameworks to develop three novel autonomous path-following systems: i) a lighting-resistant system capable of autonomous operation across daily lighting change through the fusion of data from traditional-grayscale and colorconstant images, ii) a multi-stereo system that extends the field-of-view of the algorithm by fusing data from multiple stereo cameras, and iii) a multi-experience system that uses both localization frameworks to achieve reliable localization across appearance change as extreme as night vs. day and winter vs. summer. These systems are validated through a collection of extensive field tests covering over 213 km of vision-in-the-loop autonomous driving across a wide variety of environments and appearance change with an autonomy rate of 99.7% of distance traveled.
Formal Methods for Control Synthesis: An Optimization Perspective

In control theory, complicated dynamics such as systems of (nonlinear) differential equations are controlled mostly to achieve stability. This fundamental property, which can be with respect to a desired operating point or a prescribed trajectory, is often linked with optimality, which requires minimizing a certain cost along the trajectories of a stable system. In formal verification (model checking), simple systems, such as finite-state transition graphs that model computer programs or digital circuits, are checked against rich specifications given as formulas of temporal logics. The formal synthesis problem, in which the goal is to synthesize or control a finite system from a temporal logic specification, has recently received increased interest. In this article, we review some recent results on the connection between optimal control and formal synthesis. Specifically, we focus on the following problem: Given a cost and a correctness temporal logic specification for a dynamical system, generate an optimal control strategy that satisfies the specification. We first provide a short overview of automata-based methods, in which the dynamics of the system are mapped to a finite abstraction that is then controlled using an automaton corresponding to the specification. We then provide a detailed overview of a class of methods that rely on mapping the specification and the dynamics to constraints of an optimization problem. We discuss advantages and limitations of these two types of approaches and suggest directions for future research.
3D Model Construction of Turntable and Robotic Arm Sequence

This study is done to evaluate the factors affecting the 3D reconstruction model by using a different image acquisition technique; an autonomous rotatable robotic arm and a turntable. Two sets of sequential images were obtained using different projection angle of the camera. The silhouettebased approach is used in this study for 3D reconstruction from the sequential images captured of several different angles of the object. Other than that, an analysis based on the effect of a different number of sequential images to the accuracy of 3D model reconstruction was also carried out with a fixed projection angle of the camera. The effecting elements in the 3D reconstruction are discussed and the overall result of the analysis is concluded according to the prototype of imaging platform. It shows that, by using a robotic arm resulting with better final image reconstruction.
Identification and classification of historical Kannada handwritten document images using LBP features

Digitisation process is very much essential for historical handwritten documents due to degraded qualities in the manuscript such as ink bleed, arbitrary geometric distortions, storage conditions and age. In this work, the age-type identification and classification of historical Kannada handwritten document images is done by applying text-block wise segmentation method, extracting the LBP features and using LDA, K-NN and SVM classifiers. The purpose of the present work is to identify the document script of the dynasties, whether it belongs to Hoysala dynasty or Vijayanagara dynasty or Mysore Wodeyar's dynasty? The average classification accuracy of the proposed method with LDA classifier is 94.6%, whereas K-NN classifier yielded 98.3% and SVM classifier yielded 99.3%. As per the results obtained from the experimentation, it is proved that the SVM classifier has got good classification ability comparatively with respect to LDA and K-NN classifiers for historical Kannada handwritten document images of all age-type scripts.
Significant data region identification and analysis using k‐means in large storage drive forensics

The recent technological advancement with less implementation cost has completely changed the scenario of information being generated, stored, or manipulated digitally by using the storage devices. Today the criminal activities are directly or indirectly associated with the storage devices, thus it is now recognized as an essential evidence in court‐of‐law throughout the world. However, the massive capacities of modern storage devices significantly increase the time and effort required to preserve and analyze the evidence. This paper proposes a methodology based on the random sector sampling and k‐means clustering approaches to efficiently identify and evaluate the significant data regions instead of the entire storage drive. The random sampling and clustering methods efficiently reveal the unseen resident data pattern and intelligence about the regions of the drive which may be of investigator's interest. Experiments involving storage drives of various capacities demonstrate the efficacy of the methodology. Moreover, we generalize our discussion to represent that the extracted hidden patterns of storage drive data can assist an investigator in achieving the desired performance requirements.
Critical Search: A Procedure for Guided Reading in Large-Scale Textual Corpora

Whether they work with pages hand-selected from an archive, or keywords hand-selected from a digital corpus, scholars of all kinds wrestle with the issue of exemplarity. Cherry-picked examples leave the scholar's conclusions vulnerable to charges of, at best, irrelevance, and at worst, malfeasance. In digital research, even seemingly simple queries are plagued with these pitfalls, which can only be addressed by critical thinking about the queries we propose, the algorithms we use, and the questions we ask of them. If digital research is approached responsibly, however, it allows the scholar to choose exemplary texts for reading with a precision and clarity unavailable to previous generations.
False-negative serologic tests for Toxoplasma in birds.

Epidemiologic studies for Toxoplasma infection often rely unquestioningly on serologic tests as if necessarily they were sensitive indicators of past or present infection. To compound the problem, the sera are often screened at higher dilutions than are generally found positive in birds. In a recent study of animals in Florida (Burridge et al., 1979, AJVMA 175: 964-967) the indirect hemagglutination test was used at at dilution of 1:64. Positive tests were found in 8.4% of 2,179 mammals, ranging between 11 and 19% in opossums, rats, raccoons, and armadillos. However, only 0.6% of 1,279 bird sera were reactive. This was interpreted that ". birds appear to have a minor role in the maintenance of T. gondii infection in Florida. " In a similar survey in California, though using a kit of a different manufacturer, antibody reactivity was found in 14.4% of 1,132 mammals but only in 4.4% of 125 birds (Franti et al., 1975, JAVMA 167: 565-568). There are several isolated observations on finding low, transient or unmeasurable antibody titers in experimentally infected chickens using dye, complement-fixation or fluorescent antibody tests (Jones et al., 1959, J. Parasit. 45: 31-37; Boch et al., 1966, Berl. Munch. Tierarztl Wchsch., 79: 352-356). A recent study in an epidemiologic setting illustrates the insensitivity of usual serologic methods to detect Toxoplasma infection in chickens and sparrows (Ruiz and Frenkel, 1980, Am. J. Trop. Med. Hyg. 29: 1161-1166). Toxoplasma was isolated from brain or skeletal muscle from 54% of 50 chickens from Costa Rican farms and from 16% of 106 sparrows all of which were seronegative in the dye test at 1:2. By comparison, 11% of 107 rats had antibody and Toxoplasma was isolated from 12.5%; also, 6% of 202 mice had antibody and Toxoplasma was isolated from 3.5% by passaging brain. Whereas serologic tests in rats and mice were reasonably sensitive in predicting infection, this was not so in chickens and sparrows which actually had a higher infection rate than the mammals tested.
Spectrum Sensing and Mitigation of Primary User Emulation Attack in Cognitive Radio

The overwhelming growth of wireless communication has led to spectrum shortage issues. In recent days, cognitive radio (CR) has risen as a complete solution for the issue. It is an artificial intelligence-based radio which is capable of finding the free spectrum and utilises it by adapting itself to the environment. Hence, searching of the free spectrum becomes the key task of the cognitive radio termed as spectrum sens- ing. Some malicious users disrupt the decision-making ability of the cognitive radio. Proper selection of the spectrum scheme and decision-making capability of the cogni- tive reduces the chance of colliding with the primary user. This chapter discusses the suitable spectrum sensing scheme for low noise environment and a trilayered solution to mitigate the primary user emulation attack (PUEA) in the physical layer of the cognitive radio. The tag is generated in three ways. Sequences were generated using DNA and chaotic algorithm. These sequences are then used as the initial seed value for the generation of gold codes. The output of the generator is considered as the authentica - tion tag. This tag is used to identify the malicious user, thereby PUEA is mitigated. Threat-free environment enables the cognitive radio to come up with a precise decision about the spectrum holes.
Science Track FrOSCon 2016

Im Jahre 2015 feierte die Free and Open Source Software Conference ihr 10 Jahriges Bestehen. Entstanden aus einer Idee von Studierenden, wissenschaftlichen Mitarbeitern und Professoren des Fachbereichs Informatik entwickelte sich eine der wichtigsten Konferenzen im Bereich der freien und quelloffenen Software in Deutschland.
Stability of Antihypertensive Peptides from Egg White Protein to Chemicals and Enzymes

The stability of antihypertensive peptides from egg white protein to chemicals was evaluated by Plackett-Burman design and its stability in mimic gastrointestinal environment was also investigated by determining angiotensin converting enzyme activity.Results indicated that pH,temperature,light illumination,stock peptide concentration,Pasteurization treatment,ultrasonic treatment and magnesium ions had no significant effect on the stability of antihypertensive peptides.However,the stability of antihypertensive peptides was sensitive to pepsin and trypsin.The activity of antihypertensive peptides decreased to 13.0 % and 4.0 % from 46.0 %.
Jacquard Control System of Warp Knitting Machine Based on Embedded System

In order to improve the control precision and speed, jacquard control system of warp knitting machine is designed using Embedded System. Based the overall design of the jacquard control system, the hardware and software are designed respectively. Industrial Ethernet is used to complete the data transmission in the system, aiming to improve the capacity and reliability for high speed data transmission. The synchronous control of the yarn guide pin is based on the distributed clock algorithm. The designed control system can simultaneously control multi-jacquard with faster speed and higher stability.
Association between the rs3795879 G/A polymorphism of the SERPINE2 gene and chronic obstructive pulmonary disease: a meta-analysis.

: The present study aimed to investigate the effects of the rs3795879 polymorphism of the SERPINE2 gene on the development of chronic obstructive pulmonary disease (COPD) based on a systematic meta-analysis. An extensive literature search was performed to retrieve previously published case-control studies on the polymorphisms of SERPINE2 in COPD patients. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the association between SERPINE2 polymorphisms and risk of developing COPD. A total of 5 studies including 3034 COPD cases and 3068 controls were incorporated in the present meta-analysis. Generally, no significant association was identified between the rs3795879 polymorphism of SERPINE2 and the risk of developing COPD (G allele vs A allele: OR = 1.23, 95%CI = 0.97-1.32; GG vs GA: OR = 1.19, 95%CI = 0.81-1.76; GG vs AA: OR = 1.23, 95%CI = 0.89-1.70; dominant model: OR = 1.18, 95%CI = 0.85- 1.62; recessive model: OR = 1.19, 95%CI = 0.85-1.66). In addition, subgroup analyses according to different ethnicities and the source of controls suggest no statistically significant association between the rs3795879 polymorphism of SERPINE2 and COPD risk. The results suggest that the rs3795879 polymorphism of SERPINE2 is not a risk factor for COPD.
Probabilistic analysis of adaptive experimental designs

Un ensayo clinico es un experimento estadistico que consiste en comparar el comportamiento de dos tratamientos con objeto de establecer la superioridad de uno respecto al otro. En esta tesis se ha presentado un nuevo diseno de ensayo clinico adaptado a la respuesta, llamado diseno urna de Klein, que intenta combinar buenas propiedades eticas e inferenciales. A s vez, se han estudiado sus propiedades exactas y asintoticas y se compara el nuevo diseno con otros disenos destacados en la literatura estadistica. Se realiza un estudio detallado de inferencia basado en la aleatorizacion desde un punto de vista exacto y asintotico. Finalmente, se analiza la inclusion de variables en el diseno.
FACIAL EXPRESSION RECOGNITION BASED ON PRINCIPAL COMPONENTS ANALYSIS

Abstract: Recognizing facial expression is one of the most effective applications of image processing and has obtained great attention in latest years. A recognition system for facial expression is a computer based application which detects an individual facial expression for the purposes of authentication, criminal identification, passport verification, estimating age, and various other purposes. In this study, we propose a human recognition system based on facial expression. The system depends on extracting features using Principal Component Analysis (PCA) which later used in the training and recognition steps. The system is able to recognize diverse facial expressions such as Neutral, Anger, Disgust ,Fear, Happy, Sad and Surprise. The primary objective of this study is to improve the efficiency and to achieve better recognition rate using Support Vector Machine (SVM). The system is evaluated using the registered JAFFE Dataset of face images. The results show that or proposed system is robust and maintain high recognition rate.
Real-time automatic transport mode detection on smartphones using Recurrent Neural Networks

Innovative transport solutions using ITS (Intelligent Transport Systems). The activity aims at defining innovative transport solutions using ITS (Intelligent Transport Systems) both at city (Compiegne) and regional level (Region Hauts de France) to maximize multimodality and improve the socio-economic development of the territory. For example, finding out new methods for collecting mobility data (and notably big data) from different sources could help in understanding the mobility patterns and propose tailored solutions at different geographical scales. Another example regards the design of “mobility as a service” where packages of services can be offered focusing also on the integrated ticketing.