Miracle-dz/UniFAR-FTUs huggingface dataset:
ID-based password authentication scheme using smart cards and fingerprints

This paper proposes two ID-based password authentication schemes, which does not require a dictionary of passwords or verification tables, with smart card and fingerprint. In these schemes, users can change their passwords freely. For a network without synchronization clocks, the proposed nonce-based authentication scheme can withstand message replay attacks. The proposed two schemes require a system to authenticate each user by each user's knowledge, possession, and biometrics, and this feature makes our schemes more reliable.
First-Person Activity Forecasting with Online Inverse Reinforcement Learning

We address the problem of incrementally modeling and forecasting long-term goals of a first-person camera wearer: what the user will do, where they will go, and what goal they seek. In contrast to prior work in trajectory forecasting, our algorithm, DARKO, goes further to reason about semantic states (will I pick up an object? ), and future goal states that are far in terms of both space and time. DARKO learns and forecasts from first-person visual observations of the user’s daily behaviors via an Online Inverse Reinforcement Learning (IRL) approach. Classical IRL discovers only the rewards in a batch setting, whereas DARKO discovers the states, transitions, rewards, and goals of a user from streaming data. Among other results, we show DARKO forecasts goals better than competing methods in both noisy and ideal settings, and our approach is theoretically and empirically no-regret.
Fast 3D face modeling using mesh optimization and vertex integration

3D animation is a field in computer graphics with vibrant recent research activities, and one of the important research areas in 3D animation is animating the human being. Animation production using 3D faces has traditionally involved the animator conducting frame-by-frame manual work, requiring much effort, time, equipment and 3D software. This paper describes the implementation process of creating a fast and simple 3D face model that resembles the actual human face by inputting the frontal facial image, and suggests a technique for simplifying the mesh data of the general 3D model.
ARMageddon: Last-Level Cache Attacks on Mobile Devices

In the last 10 years cache attacks on Intel CPUs have gained increasing attention among the scientific community. More specifically, powerful techniques to exploit the cache side channel have been developed. However, so far only a few investigations have been performed on modern smartphones and mobile devices in general. In this work, we describe Evict+Reload, the first access-based cross-core cache attack on modern ARM Cortex-A architectures as used in most of today’s mobile devices. Our attack approach overcomes several limitations of existing cache attacks on ARM-based devices, for instance, the requirement of a rooted device or specific permissions. Thereby, we broaden the scope of cache attacks in two dimensions. First, we show that all existing attacks on the x86 architecture can also be applied to mobile devices. Second, despite the general belief these attacks can also be launched on non-rooted devices and, thus, on millions of off-the-shelf devices. Similarly to the well-known Flush+Reload attack for the x86 architecture, Evict+Reload allows to launch generic cache attacks on mobile devices. Based on cache template attacks we identify information leaking through the last-level cache that can be exploited, for instance, to infer tap and swipe events, inter-keystroke timings as well as the length of words entered on the touchscreen, and even cryptographic primitives implemented in Java. Furthermore, we demonstrate the applicability of Prime+Probe attacks on ARM Cortex-A CPUs. The performed example attacks demonstrate the immense potential of our proposed attack techniques.
Are estimated control charts in control?

Standard control chart practice typically assumes normality and uses estimated parameters using data from an in-control process. However, because of the extreme quantiles involved, large relative errors will result for common performance characteristics such as the out-of-control signal probability or the average run length. Due to the estimation, such performance characteristics are stochastic and hence the relative errors involved can be analyzed in various ways. To assess the effects of these various ways of estimation, we look at some exceedance probabilities. It is demonstrated how corrections can be derived to bring the estimated false alarm rates close to their nominal values. Exact results are given, followed by simple approximations. The latter reveal the way in which the corrections depend on the underlying parameters, thus allowing a sensible approach in practice. Some illustration is provided, as well as a brief analysis of the out-of-control behavior of the corrected charts.
Joint image reconstruction and sensitivity estimation in SENSE (JSENSE)

Parallel magnetic resonance imaging (pMRI) using multichannel receiver coils has emerged as an effective tool to reduce imaging time in various applications. However, the issue of accurate estimation of coil sensitivities has not been fully addressed, which limits the level of speed enhancement achievable with the technology. The self‐calibrating (SC) technique for sensitivity extraction has been well accepted, especially for dynamic imaging, and complements the common calibration technique that uses a separate scan. However, the existing method to extract the sensitivity information from the SC data is not accurate enough when the number of data is small, and thus erroneous sensitivities affect the reconstruction quality when they are directly applied to the reconstruction equation. This paper considers this problem of error propagation in the sequential procedure of sensitivity estimation followed by image reconstruction in existing methods, such as sensitivity encoding (SENSE) and simultaneous acquisition of spatial harmonics (SMASH), and reformulates the image reconstruction problem as a joint estimation of the coil sensitivities and the desired image, which is solved by an iterative optimization algorithm. The proposed method was tested on various data sets. The results from a set of in vivo data are shown to demonstrate the effectiveness of the proposed method, especially when a rather large net acceleration factor is used. Magn Reson Med 57:1196–1202, 2007. © 2007 Wiley‐Liss, Inc.
Efficiency Tests in the Art Market Using Cointegration and the Error Correction Model

I aim to understand art prices and returns from a market efficiency point of view and we seek to understand whether the art market exhibits predictability or randomness. I tested the weak-form efficiency random walk using ADF and found that most of my time-series data are non-stationary; hence, they all possess randomness. I proceeded and tested my art data using cointegration and the ECM by comparing them to non-risky and risky asset as well as an economic indicator. To be market-efficient, I cannot reject the null hypothesis and accept the alternative hypotheses of cointegrated data. Thus, the results are mixed – art market behaviour can be partly forecasted. I can predict the outcome of art using gold as a benchmark. Bonds are not useful predictors for the art market. Oil & gas as well as the GDP are good predictors of the general art market. The implications of market efficient are mixed. Art can be used as hedge when bundled with bonds. Portfolio diversification seems to be less favourable for the art market. The way to profit is to look at the returns of oil & gas, assuming other people do not possess this information. My study contradicted the academic belief of market efficiency in favour of practitioners. Subjected to scrutiny, my mixed results do not suggest fully abandoning the notion of efficiency in the art market.
CONTROL OF MECHATRONIC SYSTEMS

No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, without either the prior written permission of the Authors. Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herin may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.
Guidelines for Verification of Population Protocols

—We address the problem of veriﬁcation by model- checking of basic population protocol (PP) model of Angluin et al. This problem has received special attention the last two years and new tools have been proposed to deal with. We show that the problem can be solved using the existing model- checking tools, e.g., Spin and Prism. For this, we apply the counting abstraction to obtain an abstract model of a PP which can be efﬁciently veriﬁed by the existing model-checking tools. Moreover, this abstraction is preserves the correct stabilization property of PP. To deal with the fairness assumed in the PP model, we provide two recipes. The ﬁrst one gives sufﬁcient conditions under which the PP fairness can be replaced by the weak fairness implemented in Spin. We show that this recipe can be applied to several PP models. In the second recipe, we show how to use the probabilistic model-checking and the tool Prism to deal completely with the PP fairness. The correctness of this recipe is based on existing theorems on ﬁnite discrete Markov chains.
Optimization by Stochastic Methods

Self-contained examination guide and information storage apparatus comprising a flat rectangular enclosure (30) having a front panel (32) with first display arrays (34) along side edges of the front panel associated with a plurality of general patient examination categories, and an LCD (40) centrally positioned on the front panel and configured to comprise a plurality of individually controllable display segments. A microprocessor-based controller (64) includes a light pen (80) for reading bar codes on the enclosure front panel and thereby selecting among the general examination categories. A microcontroller memory has prestored sets of specific examination indicia associated with each of the general examination categories, and is responsive to the category-selection process for retrieving from memory a specific set of examination indicia associated with the selected general examination category. The light pen is then employed to scan bar code arrays (42) adjacent to the specific examination indicia at each LCD segment for identifying specific indicia of interest and loading corresponding indicia information into microcontroller memory. Information so stored may be selectively downloaded to a central computer (14) for processing and generation of records for the patient files.
The Plastomes of Two Species in the Endoparasite Genus Pilostyles (Apodanthaceae) Each Retain Just Five or Six Possibly Functional Genes

The 23 species of mycoheterotrophic or exoparasitic land plants (from 15 genera and 6 families) studied so far all retain a minimal set of 17 of the normally 116 plastome genes. Only Rafflesia lagascae, an endoparasite concealed in its host except when flowering, has been reported as perhaps lacking a plastome, although it still possesses plastid-like compartments. We analyzed two other endoparasites, the African Apodanthaceae Pilostyles aethiopica and the Australian Pilostyles hamiltonii, both living inside Fabaceae. Illumina and 454 data and Sanger resequencing yielded circularized plastomes of 11,348 and 15,167 bp length, with both species containing five possibly functional genes (accD, rps3, rps4, rrn16, rrn23) and two/three pseudogenes (rpoC2 in P. aethiopica and rpl2 and rps12 in both species; rps12 may be functional in P. hamiltonii). Previously known smallest land plant plastomes contain 27–29 genes, making these Apodanthaceae plastomes the most reduced in size and gene content. A similar extent of divergence might have caused the plastome of Rafflesia to escape detection. The higher plastome degeneration in both these families of endoparasites, Rafflesiaceae and Apodanthaceae, of similar high age, compared with exoparasites points to a difference of plastome function between those two modes of parasitic life.
Multi-stage beamforming codebook for 60GHz WPAN

Beamforming(BF) based on codebook is regarded as an attractive solution to resolve the poor link budget of millimeter-wave 60GHz wireless communication. Because the number of the elements of antenna array in 60GHz increases, the beam patterns generated are more than common BF, and it causes long set-up time during beam patterns searching. In order to reduce the set-up time, three stages protocol, namely the device (DEV) to DEV linking, sector-level searching and beam-level searching has been adopted by the IEEE 802.15. 3c as an optional functionality to realize Gbps communication systems. However, it is still a challenge to create codebook of different patterns to support three stages protocol from common codebook of beam pattern. In this paper, we proposes a multi-stage codebook design and the realization architecture to support three stages BF. The multi-stage codebook can create different granularity of beam patterns and realize progressive searching. Simulation results for eight elements uniform linear array (ULA) show that this design can divide the beam searching to three stages searching without increasing the system complexity.
Computing NFA Intersections in Map-Reduce

Nondeterministic Finite-state Automata (NFA) are simple, yet powerful devices that model a plethora of computationally oriented phenomena. One of the advantages of NFA’s is that they are closed under several operations, such as concatenation, intersection, difference, and homomorphic images. This makes NFA’s ideally suited for a modular approach, for instance in the context of protocol design and web service composition. A simple, but illustrative example of an e-commerce application designed from components can be found in Chapter 2 in [5]. The salient operation here is the intersection of several finite state automata. Problems relating to NFA’s have been widely studied in the literature. One of the main issues for the NFA intersection problem is that the size of the output NFA is the product of the size of all input NFA’s. There is not much hope for improvement, since testing for emptiness of the intersection of a set languages represented by NFA’s is known to be PSPACE-complete [8]. The most commonly used algorithm for computing the intersection NFA is to use the Cartesian construct for product automata. If there are m input NFA’s each having n states, the product NFA will have n states. It therefore would be important to come up with good distributed algorithms for the problem. Google introduced map-reduce as a parallel programming model [4] that can work over large clusters of commodity computers. Map-reduce provides a high-level framework for designing and implementing such parallelism. A growing number of papers deal with mapreduce algorithms for various problems, for instance related to graphs [12, 9, 3, 11], and related to relational joins [2, 6, 7]. In this paper we investigate the problem of implementing the Cartesian construct in map-reduce. We follow the optimization approach of Afrati et al. [1] and analyze the replication rate required for computing the
An Efficient TCAM-Based Implementation of Multipattern Matching Using Covered State Encoding

This paper proposes a state encoding scheme called a covered state encoding for the efficient TCAM-based implementation of the Aho-Corasick multipattern matching algorithm, which is widely used in network intrusion detection systems. Since the information of failure transitions of the Aho-Corasick Nondeterministic Finite Automata (NFA) is implicitly captured in the covered state encoding and the failure transition entries can be completely eliminated, the Aho-Corasick NFA can be implemented on a TCAM with smaller number of entries than other schemes. We also propose constructing the modified Aho-Corasick NFA for multicharacter processing, which can be implemented on a TCAM using the covered state encoding. The implementation of modified Aho-Corasick NFA using the covered state encoding is also superior to other schemes in both TCAM memory requirement and lookup speed.
Tracking Functional Brain Changes in Patients with Depression under Psychodynamic Psychotherapy Using Individualized Stimuli

Objective Neurobiological models of depression posit limbic hyperactivity that should normalize after successful treatment. For psychotherapy, though, brain changes in patients with depression show substantial variability. Two critical issues in relevant studies concern the use of unspecific stimulation experiments and relatively short treatment protocols. Therefore changes in brain reactions to individualized stimuli were studied in patients with depression after eight months of psychodynamic psychotherapy. Methods 18 unmedicated patients with recurrent major depressive disorder were confronted with individualized and clinically derived content in a functional MRI experiment before (T1) and after eight months (T2) of psychodynamic therapy. A control group of 17 healthy subjects was also tested twice without intervention. The experimental stimuli were sentences describing each participant's dysfunctional interpersonal relationship patterns derived from clinical interviews based on Operationalized Psychodynamic Diagnostics (OPD). Results At T1 patients showed enhanced activation compared to controls in several limbic and subcortical regions, including amygdala and basal ganglia, when confronted with OPD sentences. At T2 the differences in brain activity between patients and controls were no longer apparent. Concurrently, patients had improved significantly in depression scores. Conclusions Using ecologically valid stimuli, this study supports the model of limbic hyperactivity in depression that normalizes after treatment. Without a control group of untreated patients measured twice, though, changes in patients' brain activity could also be attributed to other factors than psychodynamic therapy.
The JMT Simulator for Performance Evaluation of Non-Product-Form Queueing Networks

This paper describes JSIM: the simulation module of the Java Modelling Tools (JMT), an open-source fully-portable Java suite for capacity planning studies. The simulator has been purposely developed to help both unexperienced and advanced users. Most of the difficult decisions that are needed in order to run simulations properly, such as the detection of the transient part of samples to be discarded, have been automated. The tool also provides guidance over the graphical design of the network and over the analysis and the plot of the results. What-if parametric analyses for parametric evaluation of complex systems are supported. Several features that increase the generality of the applications to capacity planning studies are provided, among them fork-join service centers, regions with finite capacity, state-dependent routing algorithms, priority classes and import of real workload distributions from log files
Window-Object Relationship Guided Representation Learning for Generic Object Detections

In existing works that learn representation for object detection, the relationship between a candidate window and the ground truth bounding box of an object is simplified by thresholding their overlap. This paper shows information loss in this simplification and picks up the relative location/size information discarded by thresholding. We propose a representation learning pipeline to use the relationship as supervision for improving the learned representation in object detection. Such relationship is not limited to object of the target category, but also includes surrounding objects of other categories. We show that image regions with multiple contexts and multiple rotations are effective in capturing such relationship during the representation learning process and in handling the semantic and visual variation caused by different window-object configurations. Experimental results show that the representation learned by our approach can improve the object detection accuracy by 6.4% in mean average precision (mAP) on ILSVRC2014. On the challenging ILSVRC2014 test dataset, 48.6% mAP is achieved by our single model and it is the best among published results. On PASCAL VOC, it outperforms the state-of-the-art result of Fast RCNN by 3.3% in absolute mAP.
Generative versus discriminative methods for object recognition

Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the distribution of the image features is modelled. Generative and discriminative methods have very different characteristics, as well as complementary strengths and weaknesses. In this paper we introduce new generative and discriminative models for object detection and classification based on weakly labelled training data. We use these models to illustrate the relative merits of the two approaches in the context of a data set of widely varying images of non-rigid objects (animals). Our results support the assertion that neither approach alone will be sufficient for large scale object recognition, and we discuss techniques for combining them.
Src family kinases play multiple roles in differentiation of trophoblasts from human term placenta

Tyrosine phosphorylation plays a major role in controlling many biological processes in different cell types. Src family kinases (SFKs) are one of the most studied groups of tyrosine kinases and can mediate a variety of signalling pathways. However, little is known about the expression of SFKs in human term placenta and their implication in trophoblast differentiation. Therefore, we examined the expression profile of SFK members over time in culture and their implication in differentiation. In vitro, freshly isolated cytotrophoblast cells, cultured in 10% fetal bovine serum (FBS), spontaneously aggregate and fuse to form multinucleated cells that resemble phenotypically mature syncytiotrophoblasts, that concomitantly produce human chorionic gonadotropin (hCG) and human placental lactogen (hPL). In this study, we showed that trophoblasts expressed all SFK members and some of them are expressed as different splice variants. Moreover, using real‐time PCR, this study showed two different expression profiles of SFKs in human trophoblasts during culture. In addition, the protein level and phosphorylation status of Src were evaluated using specific antibodies. Src was rapidly phosphorylated at Tyr‐416 and dephosphorylated at Tyr‐527 after FBS addition. Surprisingly, inhibition of SFKs by 4‐amino‐5‐(4‐chlorophenyl)‐7‐(t‐butyl) pyrazolo[3,4‐d] pyrimidine (PP2) or herbimycin A had different effects on trophoblast differentiation. While herbimycin A inhibited morphological and hormonal differentiation, PP2 stimulated hormonal differentiation and inhibited cell adhesion and spreading with no effect on cell fusion. In summary, this study showed that SFKs play different roles in trophoblast differentiation, probably depending on SFK members activated. Thus, this study increases our knowledge and understanding of pathology related to impaired trophoblast differentiation such as pre‐eclampsia and trophoblast neoplasm.