Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of partial-echo compressed sensing in MR angiography

Magnetic resonance angiography (MRA) has significant clinical applications in the diagnosis of brain diseases related to arteries vasculature. It is often performed as a three dimensional data acquisition and, therefore, long scan time is typicall required. Recently, compressed sensing holds considerable promise to accelerate MRI data acquisition by exploiting signal sparsity. In this study, partial echo compressed sensing (PECS) method is investigated to reduce the MRA data acquisition time. Partial echo combined with random undersampling along phase encoding directions is proposed to acquire MRA data, projection onto convex set (POCS) combined with soft thresholding is used to approximate the undersampled k-space data, followed by a nonlinear reconstruction to further improve the image quality. The results show that PECS method can achieve reasonably high quality MRA reconstruction using only a small fractional k-space coverage.
Exact algorithms for finding k disjoint triangles in an arbitrary graph ∗

We consider exact algorithms for the NP-complete problem of deciding whether an input graph on n vertices has k vertex-disjoint copies of a fixed graph H. For H = K3 (the triangle) we give an O(2 2k log n) algorithm, and for general H an O(2k|H| log k+2k|H| log |H|n|H|) algorithm. We introduce a preprocessing (kernelization) technique based on crown decompositions of an auxiliary graph. For H = K3 this leads to a preprocessing algorithm that reduces an arbitrary input graph of the problem to a graph on O(k) vertices in polynomial time.
Non-rigid target tracking based on 'flow-cut' in pair-wise frames with online hough forests

In conventional online learning based tracking studies, fixed-shape appearance modeling is often incorporated for training samples generation, as it is simple and convenient to be applied. However, for more general non-rigid and articulated object, this strategy may regard some background areas as foreground, which is likely to deteriorate the learning process. Recently published works utilize more than one patches to represent non-rigid object with foreground object segmentation, but most of these segmentation for target representation are performed only in single frame manner. Since the motion information between the consecutive frames was not considered by these approaches, when the backgrounds are similar to the target, accurate segmentation is hard to be achieved. In this work, we propose a novel model for non-rigid object segmentation by incorporating consecutive gradients flow between pair-wise frames into a Gibbs energy function. With help from motion information, the irregular target areas can be segmented more accurately during precise boundary convergence. The proposed segmentation model is incorporated into a semi-supervised online tracking framework for training samples generation. We test the proposed tracking on challenging videos involving heavy intrinsic variations and occlusions. As a result, the experiments demonstrate a significant improvement in tracking accuracy and robustness in comparison with other state-of-art tracking works.
Motivation and emotion in multicultural psychology

Motivation and emotion share a common theme: Both occur as a function of or in the presence of a valued object or goal. Investing attention, effort, and time into a particular goal implies value; emotioneliciting stimuli imply that the appraiser is not indifferent to that object. In this chapter, we review implications for motivation and emotion for ethnic groups in the United States. Considering motivation and emotion is a matter of elucidating differences in how members of each ethnic group may perceive different goals, priorities, and judgments in their environments. We provide a summary of the dominant theoretical frameworks in each domain that draws on research conducted in the United States and elsewhere, with the belief that these frameworks shed light on universal processes that have unique manifestations in each ethnic group. Although the intent is to focus on ethnic groups in the United States, because we draw from universal processes, much of the discussion here may apply to other countries, especially those with a Western majority.
Modelling User Collaboration in Social Networks Using Edits and Comments

Research has shown that in Q&A social networks, collaboration between respondents results in quality answers. Since good answers are required to keep any Q&A social network active, it is important to understand the characteristics of these collaborations and the collaborators. In this paper, we investigate how Stack Overflow promotes collaboration by allowing users to edit existing questions and answers in order to improve them. Using over 40,000 answer posts, our study reveals that collaboration in answer posts is not a function of achievement earned in terms of badges, as most edits associated with "best answer" rewards were posted by users who have not earned any answer badge. Our study further shows that posts that earned the "best answer" reward have more comments than those that did not. This study though, work in progress, can aid developers in implementing collaboration strategies in social networks that work.
Price of Anarchy for Routing Games with Incomplete Information

In this paper, we study a noncooperative traffic network where n users or agents need to send their traffic from a given source to a given destination overm identical, nonintersecting, parallel links. We consider a situation where each agent tries to send its traffic through the network in an entirely selfish manner, that is, aiming to minimize its individual delay. The model assumes that the amount of traffic which an agent wants to send through the network is known to the agent but not to the rest of the agents. However, each agent has a belief about the traffic loads of all other agents, expressed in terms of a probability distribution. For such a network, we wish to measure how bad selfish routing can be and this leads us to study the price of anarchy of such routing games. The model here turns out to be an incomplete information routing game, for which there are no studies yet on the price of anarchy. We develop an elegant framework for studying this by introducing the notion of traffic equations and traffic delay equations and using the solution concept of Bayesian Nash equilibrium. Our results show that the bounds on price of anarchy for incomplete information routing games are essentially the same as for complete information routing games. One possible interpretation of the results is that the worst case loss in performance due to selfish routing is not affected if the knowledge of agents about other agents is probabilistic rather than deterministic.
A Mineral Magnetic Approach to Determine Paleo‐Firing Temperatures in the Neolithic Settlement Site of Mursalevo‐Deveboaz (SW Bulgaria)

Archeological remains from the Neolithic period in SE Europe are characterized by the presence of massive burnt daub relics sintered at high temperatures. These findings raised the hypothesis of deliberate house burning as a strategy for ensuring the survival of place and the development of social memory in Neolithic society. Although highly discussed in the archeological community, analytical data on the ancient firing temperatures achieved during burning Neolithic houses are missing except an empirical study determining firing temperatures according to the color of burned clay. The Neolithic site Mursalevo‐Deveboaz (Bulgaria) is one of the largest known settlements consisting of more than 70 houses. Rock‐magnetic analyses are applied for characterization of iron oxides produced during firing, and the firing temperatures were estimated using the magnetic susceptibility method. Results on a collection of 445 samples show the presence of very fine grained magnetite/maghemite and hematite. Magnetic data are supported by elemental analysis, reflectance spectroscopy, and scanning electron microscopy. The data suggest an increase in the magnetic grain size from superparamagnetic toward single domain with increasing firing temperature. Firing temperature estimates for 148 samples of different color vary between 680 and 1,140°C. Comparing the magnetic properties of iron oxides identified and literature data on solution‐combustion synthesis of iron oxides allowed a mechanism behind the extreme firing of Neolithic houses to be suggested. Our study proposes for the first time that combustion synthesis of iron oxides could explain the extreme house burning in many Neolithic settlements achieved through intentional addition of wood, dung and urine.
TZDs Cause Bone Loss and Higher Fracture Rates in Diabetic Patients

Thiazolidinediones (TZDs) are synthetic PPARγ (peroxisome proliferator-activated receptor gamma) agonists and a class of drugs for diabetes mellitus type 2 that can decrease blood sugar efficiently by enhancing insulin sensitivity. However, increased bone fracture risk in diabetic individuals treated with TZDs is one of the reported side effects. Recent studies show that TZDs such as rosiglitazone simultaneously inhibit osteoblast differentiation and activate osteoclast differentiation, leading to bone loss due to decreased bone formation and increased bone resorption. Furthermore, TZDs may activate PPARγ in tissues other than bone, such as the hypothalamus-pituitary-gonad (HPG) axis to indirectly regulate bone mass. This paper will focus on current new developments that implicate potential mechanisms for how PPARγ modulates skeletal homeostasis and how TZDs exert bone-loss side effects.
Weighted fusion of LBP and CCH features for effective content based image retrieval

Content based image retrieval for remote sensing images is challenging research area in recent years. In this paper, the weighted image fusion algorithm of morphological feature circular covariance histogram (CCH) and local binary and tetra patterns (LBP and LTrP) is presented. These features are effective for defining the image texture content and the content of the image but has limitations in defining the overall content of the image when individual features are used. Using proposed algorithm, retrieval results are improved when the features are combined compared to retrieval results of the individual features. For a given query image, there are instances where non-relevant images are assigned better ranks than relevant images. Such instances are minimized, thus weeding them out. This minimization process results into a weight matrix, which is used for obtaining the combined distance of the query image with database images. This combined distance is finally used for ranking the images. The proposed algorithm is experimented with UC Merced LULC image data set of 2100 images with 21 classes and 100 images in each class. All the 2100 images are taken as query image at a time and performance is evaluated for each image as a query image. The retrieval results obtained using proposed algorithm is compared with results obtained using individual and combined feature set with and without weight matrix. Simulation results are evaluated based on precision gain ratio and normalized rank which is significantly improved that proves that proposed algorithm is more effective.
Polarization of the Rényi Information Dimension With Applications to Compressed Sensing

In this paper, we show that the Hadamard matrix acts as an extractor over the reals of the Rényi Information Dimension (RID), in an analogous way to how it acts as an extractor of the discrete entropy over finite fields. More precisely, we prove that the RID of an i.i. d. sequence of mixture random variables polarizes to the extremal values of 0 and 1 (corresponding to discrete and continuous distributions) when transformed by a Hadamard matrix. Furthermore, we prove that the polarization pattern of the RID admits a closed form expression and follows exactly the Binary Erasure Channel (BEC) polarization pattern in the discrete setting. We discuss the applications of the RID polarization to Compressed Sensing of i.i. d. sources. In particular, we use the RID polarization to construct a family of deterministic ±1-valued sensing matrices for Compressed Sensing. We run numerical simulations to compare the performance of the resulting matrices with that of the random Gaussian and the random Hadamard matrices. The results indicate that the proposed matrices afford competitive performances, while being explicitly constructed.
Using model knowledge for learning inverse dynamics

In recent years, learning models from data has become an increasingly interesting tool for robotics, as it allows straightforward and accurate model approximation. However, in most robot learning approaches, the model is learned from scratch disregarding all prior knowledge about the system. For many complex robot systems, available prior knowledge from advanced physics-based modeling techniques can entail valuable information for model learning that may result in faster learning speed, higher accuracy and better generalization. In this paper, we investigate how parametric physical models (e.g., obtained from rigid body dynamics) can be used to improve the learning performance, and, especially, how semiparametric regression methods can be applied in this context. We present two possible semiparametric regression approaches, where the knowledge of the physical model can either become part of the mean function or of the kernel in a nonparametric Gaussian process regression. We compare the learning performance of these methods first on sampled data and, subsequently, apply the obtained inverse dynamics models in tracking control on a real Barrett WAM. The results show that the semiparametric models learned with rigid body dynamics as prior outperform the standard rigid body dynamics models on real data while generalizing better for unknown parts of the state space.
Torrefaction of Malaysian Palm Kernel Shell into Value-Added Solid Fuels

This project aims to investigate the potential of torrefaction to improve the properties of Malaysian palm kernel shell (PKS) as a solid fuel. A study towards torrefaction of PKS was performed under various temperature and residence time of 240, 260, and 280 o C and 30, 60, and 90 minutes respectively. The torrefied PKS was characterized in terms of the mass yield, energy yield, elemental composition analysis, calorific value analysis, moisture and volatile matter contents, and ash and fixed carbon contents. The mass and energy yield changes in the torrefied PKS were observed to prove that the temperature has more effect compare to residence time in the torrefaction process. The C content of PKS increases while H and O contents decrease after torrefaction, which resulted in higher heating value between 5 to 16%. Meanwhile, torrefaction caused the ash and fixed carbon content of PKS to increase, and the moisture and volatile matter to decrease. Keywords—biomass, palm kernel shell, pretreatment, solid fuel, torrefaction
A Formal Approach to Detecting Security Flaws in Objected-Oriented Databases

SUMMARY Detecting security ﬂaws is important in order to keep the database secure. A security ﬂaw in object-oriented databases means that a user can infer the result of an unpermit-ted method only from permitted methods. Although a database management system enforces access control by an authorization, security ﬂaws can occur under the authorization. The main aim of this paper is to show an eﬃcient decision algorithm for detecting a security ﬂaw under a given authorization. This problem is solvable in polynomial time in practical cases by reducing it to the congruence closure problem. This paper also mentions the problem of ﬁnding a maximal subset of a given authorization under which no security ﬂaw exists.
Computational Complexity of Competitive Diffusion on (Un)weighted Graphs

Consider an undirected graph modeling a social network, where the vertices represent users, and the edges do connections among them. In the competitive diffusion game, each of a number of players chooses a vertex as a seed to propagate his/her opinion, and then it spreads along the edges in the graphs. The objective of every player is to maximize the number of vertices the opinion infects. In this paper, we investigate a computational problem of asking whether a pure Nash equilibrium exists in the competitive diffusion game on unweighed and weighted graphs, and present several negative and positive results. We first prove that the problem is W[1]-hard when parameterized by the number of players even for unweighted graphs. We also show that the problem is NP-hard even for series-parallel graphs with positive integer weights, and is NP-hard even for forests with arbitrary integer weights. Furthermore, we show that the problem for forest of paths with arbitrary weights is solvable in pseudo-polynomial time; and it is solvable in quadratic time if a given graph is unweighted. We also prove that the problem for chain, cochain, and threshold graphs with arbitrary integer weights is solvable in polynomial time.
Epileptic Seizure Detection Using Lacunarity and Bayesian Linear Discriminant Analysis in Intracranial EEG

Automatic seizure detection plays an important role in long-term epilepsy monitoring, and seizure detection algorithms have been intensively investigated over the years. This paper proposes an algorithm for seizure detection using lacunarity and Bayesian linear discriminant analysis (BLDA) in long-term intracranial EEG. Lacunarity is a measure of heterogeneity for a fractal. The proposed method first conducts wavelet decomposition on EEGs with five scales, and selects the wavelet coefficients at scale 3, 4, and 5 for subsequent processing. Effective features including lacunarity and fluctuation index are extracted from the selected three scales, and then sent into the BLDA for training and classification. Finally, postprocessing which includes smoothing, threshold judgment, multichannels integration, and collar technique is applied to obtain high sensitivity and low false detection rate. The proposed algorithm is evaluated on 289.14 h intracranial EEG data from 21-patient Freiburg dataset and yields a sensitivity of 96.25% and a false detection rate of 0.13/h with a mean delay time of 13.8 s.
Tagging and Morphological Disambiguation of Turkish Text

Automatic text tagging is an important component in higher level analysis of text corpora, and its output can be used in many natural language processing applications. In languages like Turkish or Finnish, with agglutinative morphology, morphological disambiguation is a very crucial process in tagging, as the structures of many lexical forms are morphologically ambiguous. This paper describes a POS tagger for Turkish text based on a full-scale two-level specification of Turkish morphology that is based on a lexicon of about 24,000 root words. This is augmented with a multiword and idiomatic construct recognizer, and most importantly morphological disambiguator based on local neighborhood constraints, heuristics and limited amount of statistical information. The tagger also has functionality for statistics compilation and fine tuning of the morphological analyzer, such as logging erroneous morphological parses, commonly used roots, etc. Preliminary results indicate that the tagger can tag about 98-99% of the texts accurately with very minimal user intervention. Furthermore for sentences morphologically disambiguated with the tagger, an LFG parser developed for Turkish, generates, on the average, 50% less ambiguous parses and parses almost 2.5 times faster. The tagging functionality is not specific to Turkish, and can be applied to any language with a proper morphological analysis interface.
Performance Improvement of TCP using Performance Enhancing Proxies &#8212; Effect of Premature ACK Transmission Timing on Throughput &#8212;

In order to improve TCP performance, a method using a PEP (performance enhancing proxy) is proposed. The PEP operates on a router along a TCP connection. When a data packet arrives at the PEP, it forwards the packet to the destination host, transmits the corresponding ACK (premature ACK) to the source host in behalf of the destination host and stores the copy of the packet into its own buffer (PEP buffer) in case of the retransmission of the packet. In this paper, under the strategy which keeps the number of packets in the PEP buffer for which premature ACKs have been returned being less than or equal to a fixed threshold value (watermark value), we investigate the relation between the watermark value and the maximum throughput. Extensive simulation runs show that the simulation results are roughly classified into two cases. One case is that the maximum throughput becomes larger for larger watermark value and becomes a constant value when the watermark value is over a value. The other case is that though the maximum throughput becomes larger for lager watermark value in the same way, it reversely decreases when the watermark value is over a value. We also show that the latter (former) case is easier to occur as the propagation delay in the input side network of the PEP becomes smaller (larger) and the propagation delay in the output side network of the PEP becomes larger (smaller) and the PEP buffer capacity becomes smaller (larger)
A simplified purification of lecithin.

A practical and easily reproducible method for preparing lecithin of a high degree of purity is urgently needed in connection with the use of lecithin in cardiolipin antigens (1, 2). Methods devised for this purpose have been published (3, 4), but the procedures, based on the classic studies of Levene and his coworkers (5, 6), were somewhat tedious and the lecithins so prepared have not always been satisfactory. Continued effort has therefore been devoted to simplifying and improving the available methods. The procedure here described has been adopted after numerous experiments in which many combinations of solvents were tried. The details are presented by describing a typical preparation of egg lecithin. The purification of lecithin occurring in such complex mixtures as tissue extracts is more difficult, and each source material can be expected to present special problems. An example is beef heart, which was actually used for most of the experiments by which the present method was developed, and the modifications found necessary for this particular case are discussed. Since egg lecithin can be purified so much more easily, it is hoped that this product can be universally substituted for beef heart lecithin in cardiolipin antigens. Comparative studies of the two lecithins from this point of view will be reported elsewhere.