Miracle-dz/UniFAR-FTUs huggingface dataset:
Coloring the square of a planar graph

We prove that for any planar graph G with maximum degree Δ, it holds that the chromatic number of the square of G satisfies χ(G2) ≤ 2Δ + 25. We generalize this result to integer labelings of planar graphs involving constraints on distances one and two in the graph. © 2002 Wiley Periodicals, Inc. J Graph Theory 42: 110–124, 2003
Dynamic Background Subtraction Based on Local Dependency Histogram

Traditional background subtraction methods perform poorly when scenes contain dynamic backgrounds such as waving tree, spouting fountain, illumination changes, camera jitters, etc. In this paper, a novel and effective dynamic background subtraction method is presented with three contributions. First, we present a novel local dependency descriptor, called local dependency histogram (LDH), to effectively model the spatial dependencies between a pixel and its neighboring pixels. The spatial dependencies contain substantial evidence for dynamic background subtraction. Second, based on the proposed LDH, an effective approach to dynamic background subtraction is proposed, in which each pixel is modeled as a group of weighted LDHs. Labeling the pixel as foreground or background is done by comparing the new LDH computed in current frame against its model LDHs. The model LDHs are adaptively updated by the new LDH. Finally, unlike traditional approaches which use a fixed threshold to define whether a pixel matches to its model, an adaptive thresholding technique is also proposed. Experimental results on a diverse set of dynamic scenes validate that the proposed method significantly outperforms traditional methods for dynamic background subtraction.
Recent Advances in Superhydrophobic Electrodeposits

In this review, we present an extensive summary of research on superhydrophobic electrodeposits reported in the literature over the past decade. As a synthesis technique, electrodeposition is a simple and scalable process to produce non-wetting metal surfaces. There are three main categories of superhydrophobic surfaces made by electrodeposition: (i) electrodeposits that are inherently non-wetting due to hierarchical roughness generated from the process; (ii) electrodeposits with plated surface roughness that are further modified with low surface energy material; (iii) composite electrodeposits with co-deposited inert and hydrophobic particles. A recently developed strategy to improve the durability during the application of superhydrophobic electrodeposits by controlling the microstructure of the metal matrix and the co-deposition of hydrophobic ceramic particles will also be addressed.
Building Thai WordNet with a Bi-directional Translation Method

This research presents a method of building Thai WordNet using an automatic bi-directional translation system with two EnglishThai dictionaries, LEXiTRON and Thiengburanathum Dictionary. The former was compiled using a corpus-based approach, whilst the latter was compiled on the basis of the author’s expertise. The results show that using LEXiTRON gives an F-measure of 50.36 for synset aspect, and 25.01 for word aspect, while using the Thiengburanathum Dictionary results in F-measure of 64.51 for synset aspect and 34.54 for word aspect. Furthermore, for a combination of two dictionaries, the F-measure increases to 67.16 for synset aspect and 36.27 for word aspect.
Expressive Distortion of Strokes and 3D Meshes

We introduce methods for applying two-dimensional distortions in a manner that allows us to create three-dimensional variations of stroke-based models and 3D polygonal meshes. These variations can be achieved interactively, supporting the creation of expressive variations of a given 3D model or of strokes generated from it. In order to allow for a seamless integration into existing systems and to enable additional processing of both strokes and meshes, a pipeline approach is taken in both cases. In addition, we discuss the interaction possibilities arising from the interplay between the model orientation and the strokes or the geometry. Finally, to demonstrate the usability of the proposed methods we suggest several application domains.
Semiparametric Censored Regression Models

When data are censored, ordinary least squares regression can provide biased coefficient estimates. Maximum likelihood approaches to this problem are valid only if the error distribution is correctly specified, which can be problematic in practice. We review several semiparametric estimators for the censored regression model that do not require parameterization of the error distribution. These estimators are used to examine changes in black-white earnings inequality during the 1960s based on censored tax records. The results show that there was significant earnings convergence among black and white men in the American South after the passage of the 1964 Civil Rights Act.
Tricorder: Building a Program Analysis Ecosystem

Static analysis tools help developers find bugs, improve code readability, and ensure consistent style across a project. However, these tools can be difficult to smoothly integrate with each other and into the developer workflow, particularly when scaling to large codebases. We present Tricorder, a program analysis platform aimed at building a data-driven ecosystem around program analysis. We present a set of guiding principles for our program analysis tools and a scalable architecture for an analysis platform implementing these principles. We include an empirical, in-situ evaluation of the tool as it is used by developers across Google that shows the usefulness and impact of the platform.
Hybrid Genetic Algorithm for Design of Robust Communication Systems

A novel hybrid genetic algorithm (GA) for jointly optimizing source and channel codes is presented in this paper. The algorithm first uses GA for the coarse search of source and channel codes. An iterative search is then followed for the refinement of the coarse search. The hybrid GA enhances the robustness of the design of source and channel codes. The distributed GA scheme can also be used in conjunction with the proposed hybrid GA algorithm for further performance improvement.
The Impact of Team-Based Learning on Knowledge Development

Learning is the most important component of education. However, experts must try to improve the quality and methods of ideal learning through implementing new methods and spending educational cost to improve internal efficiency and productivity. One of the most common methods is the team-based learning. Team-based learning is considered as a strong instructional strategy to benefit from using small groups and people participating in learning and using others' experiences to attract, develop, and manage the knowledge. This learning method is based on group activities to create and develop active and more effective learning. Effective learning leads to create the knowledge, increase the ability and awareness of teachers and students, and improve the education. The literature review also mentions the concepts which have effective role on team-based learning, creating, and developing the knowledge.
Environmental Health: a Global Access Science Source Dioxin-like Activities in Serum across European and Inuit Populations

Background: Persistent organic pollutants (POPs) such as polychlorinated dibenzo-p-dioxins/furans, polychlorinated biphenyls (PCBs) and organochlorine pesticides can cause a series of adverse effects on e.g. reproduction in animals and humans, many of which involve the aryl hydrocarbon receptor (AhR). The aim of the present study was to compare the integrated serum level of AhR mediated activity among European and Inuit populations, and evaluate whether the activity was associated to the selected POP markers, 2,2',4,4',5,5'-hexachlorobiphenyl (CB-153) and 1,1-dichloro-2,2-bis(p-chlorophenyl)-ethylene (p,p'-DDE).
Data Mining Methods for the Analysis of Large Geographic Databases

Spatial data mining, i.e., discovery of interesting, implicit knowledge in spatial databases, is an important task for understanding and use of spatial data-and knowledge-bases. Statistical analysis has been the main method used for analyzing spatial data. Unfortunately, it has a number of weeknesses. In this paper, a number of methods based on knowledge discovery techniques for large databases are presented. This methods may overcome some of the weaknesses of statistical analysis. Our study is focused on ef-cient method for mining strong spatial association rules in geographic information databases. A spatial association rule is a rule indicating certain association relationship among a set of spatial and possibly some non-spatial predicates. For example, a rule \80% of gas stations in rural areas are close to highways" is a spatial association rule. A strong rule indicates that the patterns in the rule have relatively frequent occurrences in the database and strong implication relationships.
Counting the Homeless in Los Angeles County

Over the past two decades, a variety of methods have been used to count the homeless in large metropolitan areas. In this paper, we report on a recent eort to count the homeless in Los Angeles County, one that employed the sampling of census tracts. A number of compli- cations are discussed, including the need to impute homeless counts to areas ofthe Countynot sampled. We conclude that, despite their im- perfections, estimated counts provided useful and credible information to the stakeholders involved.
Folding Pathways of a Helix−Turn−Helix Model Protein

A small model polypeptide represented in atomic detail is folded using Monte Carlo dynamics. The polypeptide is designed to have a native conformation similar to the central part of the helix-turn-helix protein ROP. Starting from a β-strand conformation or two different loop conformations of the protein glutamine synthetase, six trajectories are generated using the so-called window move in dihedral angle space. This move changes conformations locally and leads to realistic, quasi-continuously evolving trajectories. Four of the six trajectories end in stable native-like conformations. Their folding pathways show a fast initial development of a helix−bend−helix motif, followed by a dynamic behavior predicted by the diffusion−collision model of Karplus and Weaver. The phenomenology of the pathways is consistent with experimental results.
Representative Sets and Irrelevant Vertices: New Tools for Kernelization

The existence of a polynomial kernel for Odd Cycle Transversal was a notorious open problem in parameterized complexity. Recently, this was settled by the present authors (Kratsch and Wahlstrom, SODA 2012), with a randomized polynomial kernel for the problem, using matroid theory to encode How questions over a set of terminals in size polynomial in the number of terminals (rather than the total graph size, which may be superpolynomially larger). In the current work we further establish the usefulness of matroid theory to kernelization by showing applications of a result on representative sets due to Lovasz (Combinatorial Surveys 1977) and Marx (TCS 2009). We show how representative sets can be used to give a polynomial kernel for the elusive Almost 2-sat problem (where the task is to remove at most k clauses to make a 2-CNF formula satisfiable), solving a major open problem in kernelization. We further apply the representative sets tool to the problem of finding irrelevant vertices in graph cut problems, that is, vertices which can be made undeletable without affecting the status of the problem. This gives the first significant progress towards a polynomial kernel for the Multiway Cut problem; in particular, we get a polynomial kernel for Multiway Cut instances with a bounded number of terminals. Both these kernelization results have significant spin-off effects, producing the first polynomial kernels for a range of related problems. More generally, the irrelevant vertex results have implications for covering min-cuts in graphs. In particular, given a directed graph and a set of terminals, we can find a set of size polynomial in the number of terminals (a cut-covering set) which contains a minimum vertex cut for every choice of sources and sinks from the terminal set. Similarly, given an undirected graph and a set of terminals, we can find a set of vertices, of size polynomial in the number of terminals, which contains a minimum multiway cut for every partition of the terminals into a bounded number of sets. Both results are polynomial time. We expect this to have further applications; in particular, we get direct, reduction rule-based kernelizations for all problems above, in contrast to the indirect compression-based kernel previously given for Odd Cycle Transversal. All our results are randomized, with failure probabilities which can be made exponentially small in the size of the input, due to needing a representation of a matroid to apply the representative sets tool.
SELF-MIXING INTERFEROMETRY AND ITS APPLICATIONS IN NONINVASIVE PULSE DETECTION

This thesis describes the laser Doppler technique based on a self-mixing effect in a diode laser to noninvasive cardiovascular pulse detection in a human wrist above the radial artery. The main applications of self-mixing interferometry described in this thesis in addition to pulse detection are arterial pulse shape and autonomic regulation measurements. The elastic properties of the arterial wall are evaluated and compared to pulse wave velocity variation at different pressure conditions inside the radial artery. The main advantages of self-mixing interferometry compared to conventional interferometers are that the measurement set up is simple, because basically only one optical component, the laser diode, is needed. The use of fewer components decreases the price of the device, thus making it inexpensive to use. Moreover, an interferometer can be implemented in a small size and it is easy to control because only one optical axis has to be adjusted. In addition, an accuracy, which corresponds to half of the wavelength of the light source, can be achieved. These benefits make this technique interesting for application to the measurement of different parameters of the cardiovascular pulse. In this thesis, measurement of three different parameters from cardiovascular pulsation in the wrist is studied. The first study considers arterial pulse shape measurement. It was found that an arterial pulse shape reconstructed from the Doppler signal correlates well to the pulse shape of a blood pressure pulse measured with a commercial photoplethysmograph. The second study considers measurement of autonomic regulation using the Doppler technique. It was found that the baroreflex part of autonomic regulation can be measured from the displacement of the arterial wall, which is affected by blood pressure variation inside the artery. In the third study, self-mixing interferometry is superimposed to evaluate the elastic properties of the arterial wall. It was found that the elastic modulus of the arterial wall increases as blood pressure increases. Correlations between measurements and theoretical values were found but deviation in measured values was large. It was noticed that the elastic modulus of the arterial wall and pulse wave velocity behave similarly as a function of blood pressure. When the arterial pressure increases, both the elastic modulus and pulse wave velocity reach higher values than in lower pressure.
A Comparative Study of Reliable Error Estimators for Pruning Regression Trees

This paper presents a comparative study of several methods for estimating the true error of tree-structured regression models. We evaluate these methods in the context of regression tree pruning. Pruning is considered a key issue for obtaining reliable tree-structured models in a real world scenario. The major step of a pruning process consists of obtaining accurate estimates of the error of alternative tree models. We evaluate experimentally four methods for obtaining these estimates in twelve domains. The goal of this evaluation was to characterise the performance of the methods in the task of selecting the best possible tree among the set of trees considered during pruning. The results of the comparison show that certain estimators lead to poor decisions in some domains. The Cross Validation variant that we have proposed achieved the best results on the set-ups we have considered.
Long Non-Coding RNA Expression Profile in the Kidneys of Male, Low Birth Weight Rats Exposed to Maternal Protein Restriction at Postnatal Day 1 and Day 10

Background Long non-coding RNAs (lncRNAs), which are involved in a variety of biological functions and aberrantly expressed in many types of diseases, are required for postnatal development. In this study, we aimed to investigate the lncRNA profiles in low birth weight (LBW) rats with reduced nephron endowment induced by the restriction of maternal protein intake. LBW by reduced nephron endowment is a risk factor for hypertension and end-stage renal disease in adulthood. Methods Kidneys were obtained from LBW rats fed a low-protein diet throughout gestation and lactation as well as from normal control rats born from dams fed normal protein diets at postnatal day 1 (p1) and 10 (p10). The total number of glomeruli in the kidneys was counted at p10. LncRNA expression profiles were analyzed by sequencing and screening using the Agilent Rat lncRNA Array. Quantitative real-time PCR (qRT-PCR) analysis of these lncRNAs confirmed the identity of some genes. Results The total number of glomeruli per kidney at p10 was significantly lower in LBW rats than in controls. A total of 42 lncRNAs were identified to be significantly differentially expressed, with fold-changes ≥2.0, between the two groups. According to correlation analysis between the differentially expressed lncRNAs and mRNAs involved in kidney development, we randomly selected a number of lncRNAs for comparison analysis between LBW and control kidneys at the two time-points, p1 and p10, using qRT-PCR. Three lncRNAs (TCONS_00014139, TCONS_00014138, and TCONS_00017119), which were significantly correlated with the mRNA expression of mitogen-activated protein kinase 4, were aberrantly expressed in LBW rats, compared with controls, at both p1 and p10. Conclusions LncRNAs are aberrantly expressed in the kidneys of LBW rats, compared with controls, during nephron development, which indicates that lncRNAs might be involved in impaired nephron endowment.
Design and Simulation of a Distributed Control Scheme for Inter-destination Media Synchronization

Inter-Destination Multimedia Synchronization(IDMS) is a key requirement to enable satisfying group shared media experiences. This paper presents the design and simulation of a Distributed Control Scheme (DCS) for IDMS. In this scheme, geographically dispersed receivers exchange(multicast) RTCP reports on their arrival and play out timing for RTP packets, and each one of them uses the collected reports from the other receivers belonging to the same logical group (or cluster) to adaptively adjust its local play out timing such that an overall synchronization status (within allowable limits) is maintained. Also, the strengths (interactivity, flexibility, scalability, and robustness) and weaknesses (traffic overhead, security) of a DCS for IDMS are discussed, in comparison with centralized approaches. Moreover, a simple technique to enhance the performance in terms of coherence when using the DCS for IDMS is proposed. Simulation results prove the effectiveness of the proposed control scheme and techniques to guarantee concurrently synchronized play outpoints for independent clusters of receivers.
On Convergence and Performance of Iterative Methods for Solving Variable Coeecient Convection-diiusion Equation with a Fourth-order Compact Diierence Scheme

We conduct convergence analysis on some classical stationary iterative methods for solving the two dimensional variable coeecient convection-diiusion equation dis-cretized by a fourth-order compact diierence scheme. Several conditions are formulated under which the coeecient matrix is guaranteed to be an M-matrix. We further investigate the eeect of diierent orderings of the grid points on the performance of some stationary iterative methods, multigrid method, and preconditioned GMRES. Three sets of numerical experiments are conducted to study the convergence behaviors of these iterative methods under the innuence of the ow directions, the orderings of the grid points, and the magnitude of the convection coeecients.
Performance Comparison of Fractional Controllers and Artificial Intelligence Techniques

Studying and applications of fractional PIDs (FO-PID) are getting popular for controlling the systems, properly. With this idea, it is aimed to unveil the advantages of FO-PID over traditional integer order PIDs (IO-PID). At the same time, in this paper, artificial intelligence techniques which are particle swarm optimization and genetic algorithm are used to determine which one have more effectiveness and to find system best parameters for both controllers. Results prove the supremacy of FO-PID controllers and PSO algorithm.
In vivo larvicidal activity of monoterpenic derivatives from aromatic plants against L 3 larvae of Anisakis simplex s

In view of the lack of an effective pharmacological treatment against human anisakiosis, a disease produced by L3 larvae of the genus Anisakis present in raw fish, we studied the in vivo larvicidal effect of certain monoterpenic derivatives against L3 of A. simplex s.l. The aldehydic monoterpene citral and the alcoholic citronellol, when they are administered together to the larvae of the nematode at the concentration of 46.90mg/0.5ml in olive oil, achieve 85.90% and 67.53% dead L3, respectively, and also stop rats suffering gastrointestinal hemorrhages produced by the larvae. r 2005 Elsevier GmbH. All rights reserved.
Network mobility route optimization with certificate-based authentication

The International Civil Aviation Organization has adopted IPv6 as the network protocol for the future Aeronautical Telecommunications Network, with Mobile IPv6 (MIPv6) as the baseline protocol to provide IP mobility. For aircraft, the Network Mobility (NEMO) extension to MIPv6 has to be considered, but this protocol does not yet provide any Route Optimization procedure, although many proposals do exist. We present a new mechanism that complements an existing Route Optimization proposal for NEMO, thus making it feasible for the aeronautical environment. This approach is based on certificates that should allow reducing signalling overhead and handover delay while providing a higher level of security.
Smith-predictor compensator for a delayed omnidirectional mobile robot

This paper deals with the discrete time control of an omnidirectional mobile robot subject to transport delays. A discrete-time model of the vehicle is obtained by considering an exact discretization of the continuous time model of the robot where the time delay induced by a communication network is considered. The path-tracking problem is addressed by means of a prediction strategy based on the well known Smith predictor compensator. The nonlinear nature of the omnidirectional mobile robot induces an approximate estimate of the future values of the systems that are used together with a feedback linearization approach to solve the tracking problem.
Network Based Cooperative Surveillance System

In this project, we worked on a network based cooperative surveillance system. It can be used to track either humans or monitor still objects for anti-theft purpose. We designed multiple ways for user to select the tracking target. The tracking algorithm is based on a Tracking-Learning-Detection pipeline. Experiment results show fast and accurate tracking performance of the system. The potential of cooperative surveillance over the internet is also demonstrated.